Services and applications for a communications network

ABSTRACT

A location system is disclosed for commercial wireless telecommunication infrastructures. The system is an end-to-end solution having one or more location centers for outputting requested locations of commercially available handsets or mobile stations (MS) based on, e.g., CDMA, AMPS, NAMPS or TDMA communication standards, for processing both local MS location requests and more global MS location requests via, e.g., Internet communication between a distributed network of location centers. The system uses a plurality of MS locating technologies including those based on: (1) two-way TOA and TDOA; (2) pattern recognition; (3) distributed antenna provisioning; (5) GPS signals, (6) angle of arrival, (7) super resolution enhancements, and (8) supplemental information from various types of very low cost non-infrastructure base stations for communicating via a typical commercial wireless base station infrastructure or a public telephone switching network. Accordingly, the traditional MS location difficulties, such as multipath, poor location accuracy and poor coverage are alleviated via such technologies in combination with strategies for: (a) automatically adapting and calibrating system performance according to environmental and geographical changes; (b) automatically capturing location signal data for continual enhancement of a self-maintaining historical data base retaining predictive location signal data; (c) evaluating MS locations according to both heuristics and constraints related to, e.g., terrain, MS velocity and MS path extrapolation from tracking and (d) adjusting likely MS locations adaptively and statistically so that the system becomes progressively more comprehensive and accurate. Further, the system can be modularly configured for use in location signaling environments ranging from urban, dense urban, suburban, rural, mountain to low traffic or isolated roadways. Accordingly, the system is useful for 911 emergency calls, tracking, routing, people and animal location including applications for confinement to and exclusion from certain areas.

RELATED APPLICATIONS

The present application is a continuation-in-part of U.S. patentapplication Ser. No. 11/464,880 filed Aug. 16, 2006, and is also acontinuation-in-part of U.S. patent application Ser. No. 11/838,213filed Aug. 13, 2007; U.S. patent application Ser. No. 11/464,880 is acontinuation-in-part of U.S. patent application Ser. No. 10/297,449,filed Dec. 6, 2002 (now U.S. Pat. No. 7,714,778) which is the U.S.National Stage filing of International Application No. PCT/US01/17957filed Jun. 4, 2001 which claims the benefit of the two applications:U.S. Provisional Application No. 60/209,278 filed Jun. 2, 2000, and U.S.Provisional Application No. 60/293,094 filed May 22, 2001; U.S. patentapplication Ser. No. 11/838,213 is a continuation-in-part of U.S. patentapplication Ser. No. 10/337,807 filed Jan. 6, 2003 which is acontinuation of Ser. No. 10/297,449, filed Dec. 6, 2002 (now U.S. Pat.No. 7,714,778) which claims the benefit of U.S. Provisional ApplicationNo. 60/349,100 filed Jan. 16, 2002. Each of the above-identifiedreferences is fully incorporated herein by reference.

FIELD OF THE INVENTION

The present invention is directed generally to a system and method forlocating people or objects, and in particular, to a system and methodfor locating a wireless mobile station using a plurality ofsimultaneously activated mobile station location estimators.

BACKGROUND

There is great interest in providing existing infrastructures forwireless communication systems with the capability for locating peopleand/or objects in a cost effective manner. Such a capability would beinvaluable in a variety of situations, especially in emergency, crimesituations and mobile commerce. There are numerous competing wirelesslocation technologies that purport to effectively locate wireless mobilestations (as used herein this term includes, e.g., mobile phones, shortmessage devices (SMS), electronic container tracking tags,micro-transceivers for personal location and/or emergency). Thesetechnologies can be generally classified as:

-   -   (a) handset centric wherein a portion of the location processing        is performed at the mobile stations, and in particular, each        such mobile station (MS) includes specialized electronics        specifically for performing location. In most cases, such        specialized electronics are for detecting and receiving        satellite (or more generally, non-terrestrial) signals that can        then be used in determining a location of the MS.    -   (b) network centric wherein the wireless communication        network(s) with which the MS is in contact handle substantially        all location specific processing. As one skilled in the art will        understand, there are various wireless location technologies        that are available such as time difference of arrival (TDOA),        time of arrival (TOA), timing advance (TA) techniques, angle of        arrival (AOA), multipath pattern matching techniques; and    -   (c) hybrid systems wherein there are specialized location        electronics at the handset, but a substantial amount of the        location processing is performed at a network site rather at the        MS. An example of such a hybrid system is what is known as        network assisted GPS systems, wherein GPS signals are obtained        at the MS (with the assistance network received information) and        GPS timing information is transmitted from the MS to the network        for performing MS location computations.

The wide variety of wireless location techniques can provide, underappropriate circumstances, the following advantages:

-   -   (a) if the techniques are used in combination, a more reliable        and accurate wireless location capability can be provided. In        particular, when an embodiment of one wireless location        technique is known to be less than satisfactory in a particular        geographic area, an alternative embodiment (or alternative        technique) can be used to obtain an MS's location(s).        Additionally, two different embodiments and/or techniques can be        applied substantially simultaneously for locating an MS. In this        latter case, a location resolver is likely needed to determine a        “most likely” resulting MS location estimate. Note, that        wireless location systems for combining wireless location        techniques is described in the following international and U.S.        patent applications which are each incorporated fully by        reference herein:        -   i. U.S. Provisional Application No. 60/025,855 filed Sep. 9,            1996        -   ii. U.S. Provisional Application No. 60/044,821, filed Apr.            25, 1997;        -   iii. U.S. Provisional Application No. 60/056,590, filed Aug.            20, 1997;        -   iv. International Application No. PCT/US97/15933 filed Sep.            8, 1997 entitled “LOCATION OF A MOBILE STATION USING A            PLURALITY OF COMMERCIAL WIRELESS INFRASTRUCTURES”        -   v. International Application No. PCT/US97/15892 filed Sep.            8, 1997; entitled “LOCATION OF A MOBILE STATION”;        -   vi. U.S. application Ser. No. 09/194,367 filed Nov. 24, 1999            entitled “Location Of A Mobile Station”;        -   vii. U.S. application Ser. No. 09/176,587 filed Oct. 21,            1998 entitled “Wireless Location System For Calibrating            Multiple Location Estimators”;        -   viii. U.S. Pat. No. 6,236,365 filed Jan. 22, 1999 entitled            “Location of a Mobile Station Using A Plurality Of            Commercial Infrastructures”;        -   ix. U.S. application Ser. No. 09/299,115 filed: Apr. 23,            1999 entitled “WIRELESS LOCATION USING MULTIPLE SIMULTANEOUS            LOCATION ESTIMATORS”; and    -   (b) if a primary wireless location technique fails (e.g., due to        an electronics malfunction), then assuming an alternative        technique is available that does not use, e.g., the        malfunctioning electronics of the primary technique, then the        alternative technique can be used for MS location.

However, the variety of wireless location techniques available is alsoproblematic for at least the following reasons:

-   -   (a) a request for an MS location can require either the        requester to know the wireless location service provider of the        geographical area where the MS is likely to be, or to contact a        location broker that is able to, e.g., determine a communication        network covering the geographical area within which the MS is        currently residing and activate (directly or through the MS's        wireless service provider) an appropriate wireless location        service. In the art, the technology enabling such a location        broker capability has been referred to as a “wireless location        gateway”. An embodiment of such a gateway is described in the        PCT/US97/15892 reference identified above;    -   (b) for communication networks relying on handset centric and/or        hybrid systems for MS location, MSs roaming from networks using        only network centric location capabilities will likely not have        the specialized electronics needed for being located and        accordingly many location related network services will not be        available such as emergency services (e.g., E911 in the U.S.).    -   (c) different location techniques have different reliability and        accuracy characteristics.

Accordingly, it would be desirable to integrate into a single wirelesslocation broker or wireless location gateway as many location techniquesas possible so that location requests can be fulfilled without therequester needing to know what location technique is used. It would befurther desirable for roaming MSs to be able to be located in coverageareas where a wireless location technique is different from the one (ormore) techniques supported in the primary subscription area for the MS.Additionally, it would be desirable to provide new applications forwhich MS location information can be applied via, e.g., a wirelesslocation gateway.

DESCRIPTION OF TERMS

The following definitions are provided for convenience. In general, thedefinitions here are also defined elsewhere in this document as well.

(1.1) The term “wireless” herein refers to digital radio signaling usingwireless protocols such as Advanced Mobile Phone Service (AMPS),Narrowband Advanced Mobile Phone Service (NAMPS), code division multipleaccess (CDMA) and Time Division Multiple Access (TDMA), Global SystemsMobile (GSM), time division multiple access (TDMA), WIFI protocols,wireless signal protocols for indoor or underground wirelesscommunication systems, as well as any radio signal protocol.(1.2) As used herein, the term “mobile station” (equivalently, MS)refers to a wireless mobile device that is at least a transmittingdevice, and in most cases is also a wireless receiving device, such as aportable radio telephony handset, or a radio tag (such as may beattached to items whose location may be desired or for identifying alocating a person associated with the tag). Note that in some contextsherein instead or in addition to the term “mobile station” or “MS”, thefollowing terms are also used: “personal station” (PS), “location unit”(LU), and mobile communications device (MCD). In general, these termsmay be considered synonymous. Examples of various MSs are identified inthe Background section above.(1.3) The terms, “wireless infrastructure” (or simply “infrastructure”),denotes one or more of: (a) a network for one or more of telephonycommunication services, (b) a collection of commonly controlledtransceivers for providing wireless communication with a plurality ofMSs, (c) the wireless Internet, (d) that portion of communicationsnetwork that receives and processes wireless communications withwireless mobile stations. In some embodiments, a wireless infrastructuremay include telephony wireless base stations or access points(collectively, referred to herein as “base stations” or “BS”s) such asthose for radio mobile communication systems based on CDMA, AMPS, NAMPS,TDMA, GPRS, GSM, WIFI systems, indoor access point systems, and hybridindoor/outdoor wireless systems. The base stations provide a network ofcooperative communication channels with an air interface to the MS,Thus, an MS user within an area serviced by the base stations may beprovided with wireless communication substantially throughout the areaby user transparent communication transfers (i.e., “handoffs”) betweenthe user's MS and these base stations in order to maintain effectivetelephony service.(1.4) The phrase, “composite wireless signal characteristic values”denotes the result of aggregating and filtering a collection ofmeasurements of wireless signal samples, wherein these samples areobtained from the wireless communication between an MS to be located andthe base station infrastructure (e.g., a plurality of networked basestations). However, other phrases are also used herein to denote thiscollection of derived characteristic values depending on the context andthe likely orientation of the reader. For example, when viewing thesevalues from a wireless signal processing perspective of radioengineering, as in the descriptions of the subsequent DetailedDescription sections concerned with the aspects of the presentdisclosure for receiving MS signal measurements from a base stationinfrastructure, the phrase typically used is: “RF signal measurements”.Alternatively, from a data processing perspective, the phrases:“location signature cluster” and “location signal data” are used todescribe signal characteristic values between the MS and the pluralityof infrastructure base stations substantially simultaneously detectingMS transmissions. Moreover, since the location communications between anMS and the base station infrastructure typically include simultaneouscommunications with more than one base station, a related useful notionis that of a “location signature” (also denoted “loc sig” herein) whichis the composite wireless signal characteristic values for signalsamples between an MS to be located and a single base station. Also, insome contexts, the phrases: “signal characteristic values” or “signalcharacteristic data” are used when either or both a locationsignature(s) and/or a location signature cluster(s) are intended.(1.5) A wireless location computational estimator may be also denotedherein as a MS location hypothesizing computational model, a “firstorder model”, a FOM, and/or a “location estimating model” as well asother terms as may be appropriate. Such an estimator is used todetermine/compute a geographical estimate of a location of at leastmobile station using wireless signals communicated between the mobilestation and one or more base stations (and/or variations thereof, e.g.,indoor access points).

SUMMARY

The present disclosure relates to a method(s) and system(s) forperforming and utilizing wireless mobile station location. Inparticular, various communications network utitities, services orapplications are disclosed herein for assisting, e.g., mobile stationusers, wherein such assistance may include: (i) assistance in purchasingitems; (ii) receiving incentives/advertising for purchasing variousitems, e.g. of interest to the user (or of interest to a social networkcontact of the user); (iii) receiving routing or navigation informationfor appropriately or “intelligently” navigating the user between, e.g.,a plurality of points of interest, while attempting to satisfy one ormore user constraints related to the route or the points of interest(changes thereto); and (iv) electronic (Internet accessible) yellow pageservices for providing custom advertising to users.

Note that for convenience, communications network utitities, services orapplications as disclosed herein will be also referred to as“applications”. Accordingly, an application for routing or navigating auser may be referred to as a “routing application”, an application forproviding incentives may be referred to as an “incentive providingapplication”, etc.

In one noteworthy routing application, hotels and other personal serviceproviders, such as auto rental agencies, hotels, resorts and cruiseships may provide an inexpensive mobile station (MS) that can be usedsubstantially only for contacting: (i) the personal service, (ii)emergency services, and/or (iii) receiving directions to return to thepersonal service. Accordingly, the MS may be wirelessly located duringoperations (ii) and (iii) via wireless communications between the MS anda local wireless service provider wherein a request to locate the MS isprovided to appropriate network equipment, and the resulting MS locationestimate is: provided to a public safety emergency center (e.g., E911)for dispatching emergency services, or provided to a mapping and routingsystem such as provided by Google Maps, and/or by Mapinfo as disclosedin the LeBlanc et. al. patent application filed Jan. 22, 1999 and havingU.S. Pat. No. 6,236,365 (which is fully incorporated herein byreference) so that the MS user may be routed safely and expeditiously toa predetermined location of the personal service. Note that datarepresenting the location of the personal service can be associated withan identification of the MS so that MS activation for (iii) aboveresults in one or more audio and/or visual presentations of directionsfor directing the user to return to the personal service.

An MS together with the wireless network with which the MS iscommunicating may also provide the MS user with the ability toexplicitly request to be substantially continuously tracked, wherein theMS tracked locations are stored for access by those having permission(e.g., the user, parents and/or associates of the user, e.g., friends,employers, etc.). Additionally, the velocity and/or expected time ofarrival at a predetermined destination may be derived from such trackingand may be provided to the user or his/her associates (e.g., employer,friends, and/or family). Further, note that this tracking andnotification of information obtained therefrom may be provided via atelephony or Internet enabled mobile station, or a mobile station inoperable communication with a short messaging service. For example, theMS registered owner may provide permissions for those able to accesssuch MS tracking information so that such information can beautomatically provided to certain associates and/or provided on requestto certain associates. Additionally, note that the MS and the MSlocation providing wireless network may also allow the MS user todeactivate such MS tracking functionality. In one embodiment, an MS usermay activate such tracking for his/her MS during working hours anddeactivate such tracking during non-working hours. Accordingly, anemployer can then track employee's whereabouts during work hours, whilethe employee is able to retain his/her location privacy when not workingalthough the employer may be still able to contact the employee in caseof an emergency during the employee's non-working time. Note, that thislocation capability and method of obtaining location information aboutan MS user while assuring privacy at other times may be useful forappropriately monitoring personnel in the military, hospitals,transportation services (e.g., for couriers, bus and taxis drivers),telecommunications personnel, emergency rescue and correctionalinstitution personnel.

In another routing related application, an MS and the MS locationproviding wireless network may provide the MS user with functionality toregister certain locations so that data representing such locations canbe easily accessed for use at a later time. For example, the MS user maybe staying at a hotel in an unfamiliar area. Accordingly, the user canrequest, via his/her MS, that his/her location at the hotel bedetermined and registered so that it is available at a later time forrouting the user back to the hotel. In fact, the user may have personallocation registrations of a plurality of locations in various cities andcountries so that when traveling the user has wireless access todirections to preferred locations such as his/her hotel, preferredrestaurants, shopping areas, scenic areas, rendezvous points, theatres,athletic events, churches, entertainment establishments, locations ofacquaintances, etc. Note, that such personal location registrationinformation may reside primarily on the user's subscriber network, butupon the MS user's request, his/her personal location registrations maybe transmitted to another network from which the user is receivingwireless services as a roamer. Moreover, any new location registrations(or deletions) may be duplicated in the user's personal registration ofthe user's subscriber network. However, in some instances an MS user maywish to retain such registered locations only temporarily while the useris in a particular area; e.g., a predetermined network coverage area.Accordingly, the MS user may indicate (or such may be the default) thata new personal location registration be retained for a particular lengthof time, and/or until a location of the user is outside the area towhich such new location registrations appear to be applicable. However,prior to deleting any such registrations, the MS user may be queried toconfirm such deletions. For example, if the MS user has new locationregistrations for the Dallas, Tex. area, and the MS user subsequentlytravels to London, then upon the first wireless location performed bythe MS user for location registration services, the MS user may bequeried as whether to save the new Dallas, Tex. location registrationspermanently, for an particular length of time (e.g. 30 days), or deleteall or selected portions thereof.

Advertising may be directed to an MS according to its location. In atleast some studies Advertising may be directed to an MS according to itslocation. MS users do not respond well to unsolicited wirelessadvertisement whether location based or otherwise. However, in responseto certain user queries for locally available merchandise, certainadvertisements may be viewed as more friendly. Thus, by allowing an MSuser to contact, e.g., a wireless advertising portal by voice or viawireless Internet, and describe certain products or services desired(e.g., via interacting with an automated speech interaction unit, aninformation search engine, etc.), the user may be able to describe andreceive (at his/her MS) audio and/or visual presentations of suchproducts or services that may satisfy such a user's request and that arenear or within a predetermined travel distance, travel time, etc. fromthe MS user's location as, e.g., determined by a wireless locationcapability.

Note that the advertising may be utilized by an intelligent electronicyellow pages which can utilize the MS user's location (and/oranticipated locations; e.g., due to roadways being traversed) togetherwith user preferences and needs (as well as other constraints) to bothintelligently respond to user requests as well as intelligentlyanticipate user preferences and needs. A block diagram showing the highlevel components of an embodiment of an electronic yellow pagescapability is disclosed herein. Such an electronic yellow pagescapability may provide advertising that is user driven in that, e.g., anMS user may be able to select advertising based on attributes such as:merchant proximity, traffic/parking conditions, the product/servicedesired, quality ratings, price, user merchant preferences,product/service availability, coupons and/or discounts. Further, the MSuser may be able to determine an ordering of advertisements presentedbased on, e.g., his/her selection inputs for categorizing suchattributes. For example, the MS user may request advertisements ofathletic shoes be ordered according to the following values: (a) within20 minutes travel time of the MS user's current location, (b) midrangein price, (c) currently in stock, and (d) no preferred merchants. Notethat in providing advertisements according to the MS user's criteria,the electronic yellow pages may have to make certain assumptions suchas: if the MS user does not specify a time for being at the merchant(and instead, provides information about when he/she will travel to themerchant from his/her current location), the electronic yellow pages maydefault the time to a range of times somewhat longer than the traveltime to the merchant. Additionally, the electronic yellow pages may alsocheck stored data on the merchant to assure that the MS user can accessthe merchant once the MS user arrives at the merchant's location (e.g.,that the merchant is open for business). Further, the MS user maydynamically, and in real time, vary such advertising selectionparameters for thereby substantially immediately changing theadvertising being provided to the user's MS. For example, the MS displaymay provide an area for entering an identification of a product/servicename wherein the network determines a list of related or complementaryproducts/services. Accordingly, if an MS user desires to purchase awedding gift, and knows that the couple to be wed are planning a trip toAustralia, then upon the MS user providing input in response toactivating a “related products/services” feature, and then inputting,e.g., “trip to Australia” (as well as any other voluntary informationindicating that the purchase is for: a gift, for a wedding, and/or aprice of less than $100.00), then the intelligent yellow pages may beable to respond with advertisements for related products/services suchas portable electric power converter for personal appliances that isavailable from a merchant local (and/or non-local) to the MS user.Moreover, such related products/services (and/or “suggestion”)functionality may be interactive with the MS user. For example, theremay be a network response to the MS user's above gift inquiry such as“type of gift: conventional or unconventional?”. Moreover, the networkmay inquire as to the maximum travel time (or distance) the MS user iswilling to devote to finding a desired product/service, and/or themaximum travel time (or distance) the MS user is willing to devote tovisiting any one merchant. Note that in one embodiment of the electronicyellow pages, priorities may be provided by the MS user as to apresentation ordering of advertisements, wherein such ordering may beby: price, quality, convenience to purchase, language spoken at themerchant, user safety concerns in traveling to or being at themerchant's location, etc.

When an MS appears to be traveling an extended distance through aplurality of areas (as determined, e.g., by recent MS locations along aninterstate that traverse the plurality of areas), an application may beaccessed by the MS user such that upon entering each new area having anew collection of location related products, services, persons ofinterest, or points of interest may become available to a user of theMS. Moreover, if the MS user has a personal profile that also isaccessible by the MS and/or the network, then advertising for localbusinesses and services that are expected to meet the MS user's tastesand needs may be made available to the user. Thus, if the MS userprefers fine Italian food but does not want to travel more than 20minutes by auto from his/her current location to reach such arestaurant, then advertisements for restaurants satisfying such criteriamay be made available to the user.

Sight seeing or touring applications may be provided for MS users,wherein repeated locations of the users MS is determined for assistingin routing the user to desired, e.g., points of interest. In particular,self guided tours may be provided by such applications, wherein theapplication is interactive with the user depending on user feedback,e.g., as to one or more points of interest the user desires to see oraccess, the time the user has available to access the points ofinterest, the estimated time needed to access the points of interest,the cost of certain points of interest.

A communications network application may provided for MSs that havephoto/video capabilities integrated therein, wherein locationinformation indicative of where a picture/video is taken using the MS(optionally also with a time/date of obtaining the picture/video data)is associated with the picture/video. Note that such locationinformation may be determined from a wireless location of a users MS. Inparticular, MS latitude-longitude coordinates may be transformed into acity address (or city area) together with a direction(s) from thelocation(s) where the picture/video was taken.

An application of a wireless location system may enable geographicvisualization applications, wherein one or more geographic areas ofinterest are presented as visual geographic images or maps withannotations thereon indicative of, e.g., a relative interest a mobilestation user may have in such geographic areas. In particular, suchgeographic areas may be color coded on a map according to an expectedinterest the user may have in different ones of the areas. For example,a mobile station user may be desirous of finding a parking space in alarge parking facility such as at an airport parking facility, municipalparking (on, e.g., downtown streets or parking garages), or a shoppingmall. If the parking facility has electronic monitoring for monitoringparking spaces therein, then parking spaces (e.g., for automobiles orother modes of transportation) can be readily identified as beingoccupied or available via such electronic monitoring so that a mobilestation user can view on his/her mobile station a map of the parkingfacility with a designated color (e.g., bright green) identifying one ormore nearby available parking spaces, and optionally providing a routeto one of the parking spaces. Of course, there may be no guarantee thatthe user will arrive at one of the parking spaces prior to it beingtaken by someone else. However, if another takes the parking space, thenthe user can be notified of the parking space's unavailabilitypotentially substantially before travelling to the un available parkingspace. Of course, in providing parking space information to the user,both the location of an empty parking space and the users locationpreferably should be known or determined so that the user may benavigated to an empty parking space. In addition to a service forlocating such empty parking spaces for users in, e.g., parking garages,shopping malls, street parking in downtown areas, etc., other servicesmay also be provided which rely on wirelessly locating mobile stationusers and/or the resources for such users. In particular, such users mayrequest notifications for assisting in locating other resources such asa nearby restaurant having a reduced (or no) wait time for service, ahotel or motel having a vacancy, a campsite at a campground, a themepark (or other) attraction having a reduced (or no) wait time.

A further communications network application for utilization by a mobilecommunications device is disclosed herein, wherein electronic coupons,discounts, promotions, etc. (collectively, referred to as “incentives”herein) may be provided to the user of the mobile communications device,e.g. at the request of the user, and generally, for a particular productor product type. Moreover, such an application may provide theseincentives according to, the users location and time sensitiveinformation in that the incentives may be dependent upon the user'sgeographic location, and may also have built-in time constraints (e.g.,an expiration time/date) which may, e.g., vary with a context indicativeof such criteria as: the user's location, previous locations of theuser, user purchasing behavior, and one or more (social) networks ofcontacts/friends of the user. In particular, the present application isdirected to providing, e.g., targeted advertising to users (e.g., alsoreferred to as “consumers” in the present context) by combining varioustechnologies to provide a system and service that:

-   -   (a) allows the consumer to become aware of a product/service in        terms of both time and location, in which the consumer shows an        interest;    -   (b) allows the system to know the at least information about the        consumer that provides some measure of predictability in terms        of what the consumer will purchase and/or has an interest        therein. Note that anonymity of the consumer may still be        maintained.    -   (c) activates techniques for obtaining information from/about        the consumer for benefiting the consumer, wherein such        information is obtained by both explicit consumer input as well        as analysis of the consumer's behavior related to contacts with        others (e.g., dissemination of incentives, as well as locations        visited by the consumer);    -   (d) provides and transmits to a consumer (e.g., via an MS        therefor) various alternatives prior to, or within a reasonable        time, of the consumer making a selection of an item to purchase        so that the consumer may benefit from such alternatives to which        the consumer is provided within a relatively short time span.        In particular, the present advertising application benefits        users/consumers by providing incentives that are more        “intelligent” or “smart” than heretofore has been provided to        users, wherein such incentives can function to both assist the        consumer in buying, as well as assisting an advertiser in        selling products in a timely and cost effective manner.

Note that for a wireless location application, a primary criteria (inone embodiment) is whether a location hypothesis represents the actuallocation where the MS was when the corresponding input data set(wireless signal measurements) were communicated between this MS and thewireless network.

Disclosed are one or more FOMs that may be generally denoted asclassification models wherein such FOMs are trained or calibrated toassociate particular composite wireless signal characteristic valueswith a geographical location where a target MS could likely generate thewireless signal samples from which the composite wireless signalcharacteristic values are derived. Further, such classification FOMshave the capability for training and retraining to automaticallymaintain the accuracy of these models even though substantial changes tothe radio coverage area may occur, such as the construction of a newhigh rise building or seasonal variations (due to, for example, foliagevariations). As used herein, “training” refers to iteratively presenting“training data” to a computational module for changing the behavior ofthe module so that the module may perform progressively better as itlearns appropriate behavioral responses to the training data.Accordingly, training may include, for example, the repeated input oftraining data to an artificial neural network, or repeated statisticalregression analyses on different and/or enhanced training data (e.g.,statistical sample data sets). Note that other embodiments of a trainedpattern matching FOMs for wireless location are disclosed in U.S. Pat.No. 6,026,304, titled “Radio Transmitter Location Finding for WirelessCommunication Network Services and Management,” filed Jan. 8, 1997 andissued Feb. 15, 2000, having Hilsenrath and Wax as inventors, thispatent being incorporated herein fully by reference.

It is known in the wireless telephony art that the phenomenon of signalmultipath and shadow fading renders most analytical locationcomputational techniques such as time-of-arrival (TOA) ortime-difference-of-arrival (TDOA) substantially error prone in urbanareas and particularly in dense urban areas without further statisticalcorrelation processing such as such super resolution as disclosed inU.S. Pat. No. 5,890,068 by Fattouche et. al. issued on Mar. 30, 1999 andincorporated fully herein by reference. Moreover, it may be the casethat even though such additional processing is performed, the multipathphenomenon may still be problematic. However, this same multipathphenomenon also may produce substantially distinct or peculiar signalmeasurement patterns, wherein such a pattern coincides with a relativelysmall geographical area. Thus, a FOM(s) may utilize multipath as anadvantage for increasing accuracy. Moreover, it is worthwhile to notethat the utilization of classification FOMs in high multipathenvironments is especially advantageous in that high multipathenvironments are typically densely populated. Thus, since suchenvironments are also capable of yielding a greater density of MSlocation signal data from MSs whose actual locations can be obtained,there can be a substantial amount of training or calibration datacaptured for training or calibrating such classification FOMs and forprogressively improving the MS location accuracy of such models.

Classification FOMs may be utilized that determine target MS locationsby correlating and/or associating network anomalous behavior withgeographic locations where such behavior occurs. That is, networkbehaviors that are problematic for voice and/or data communication maybe used advantageously for locating a target MS. For example, it is wellknown that wireless networks typically have within their coverage areaspersistent subareas where voice quality is problematic due to, e.g.,measurements related to high total errors, a high error rate, or changein error rate. In particular, such measurements may be related to frameerror rates, redundancy errors, co-channel interference, excessivehandoffs between base stations, and/or other call quality measurements.Additionally, measurements may be used that are related to subareaswhere wireless communication between the network and a target MS is notsufficient to maintain a call (i.e., “deadzones”). Thus, informationabout such so called problematic behaviors may used by, e.g., a locationestimator (FOM) to generate a more accurate estimate of a target MS. Forexample, such network behavioral measurements may be provided fortraining an artificial neural network and/or for providing to astatistical regression analysis technique and/or statistical predictionmodels (e.g., using principle decomposition, partial least squares, orother regression techniques) for associating or correlating suchmeasurements with the geographic area for which they likely derive.Moreover, note that such network behavioral measurements can also beused to reduce the likelihood of a target MS being in an area if suchmeasurements are not what would be expected for the area.

FOMs themselves may be hybrid combinations of MS location techniques.For example, an embodiment may include a FOM that uses a combination ofTime Difference of Arrival (TDOA) and Timing Advance (TA) locationmeasurement techniques for locating the target MS, wherein such atechnique may require only minor modifications to the wirelessinfrastructure. In particular, such a FOM may provide reduced MSlocation errors and reduced resolution of ambiguities than are presentwhen these techniques are used separately. One embodiment of such a FOM(also denoted the Yost Model or FOM herein) is disclosed in U.S. Pat.No. 5,987,329 filed Jul. 30, 1997 and issued Nov. 16, 1999 having Yostand Panchapakesan as inventors, this patent being fully incorporatedherein by reference.

Additionally, note that FOMs related to the Yost Model may also be usedwith an elliptical search restriction location technique may also beutilized. In particular, such a technique is disclosed in U.S. patentapplication, having U.S. Ser. No. 08/903,551, and entitled “System andMethod Using Elliptical Search Area Coverage in Determining the Locationof a Mobile Terminal”, filed Jul. 30, 1997, which is also incorporatedby reference herein.

A plurality of stationary, low cost, low power “location detection basestations” (LBS) may be used in locating a MS, each such LBS having bothrestricted range MS detection capabilities, and a built-in MS.Accordingly, a grid of such LBSs can be utilized for providing wirelesssignaling characteristic data (from their built-in MSs) for: (a)(re)training such classification FOMs, and (b) calibrating the FOMs sothat each generated location hypothesis has a reliable confidence value(probability) indicative of the likeliness of the target MS being in anarea represented by the location hypothesis.

Personal communication systems (PCS) offer an appropriate localized baseupon which to build various personal location systems (PLS) forutilizing the wireless location techniques and applications disclosedherein, in particular, for locating people and/or objects.

Techniques and applications disclosed herein may include components(e.g., FOMs) that can substantially automatically retrain themselves tocompensate for variations in wireless signal characteristics (e.g.,multipath) due to environmental and/or topographic changes to ageographic service area. For example, there may be low cost, low powerbase stations, denoted location base stations (LBS) above, providing,for example, CDMA pilot channels to a very limited area about each suchLBS. The location base stations may provide limited voice trafficcapabilities, but each is capable of gathering sufficient wirelesssignal characteristics from an MS within the location base station'srange to facilitate locating the MS. Thus, by positioning the locationbase stations at known locations in a geographic region such as, forinstance, on street lamp poles and road signs, additional MS locationaccuracy can be obtained. That is, due to the low power signal output bysuch location base stations, for there to be signaling controlcommunication (e.g., pilot signaling and other control signals) betweena location base station and a target MS, the MS must be relatively nearthe location base station. Additionally, for each location base stationnot in communication with the target MS, it is likely that the MS is notnear to this location base station. Thus, by utilizing informationreceived from both location base stations in communication with thetarget MS and those that are not in communication with the target MS,the possible geographic areas within which the target MS is likely to bemay be substantially narrowed. Further, by providing each location basestation (LBS) with a co-located stationary wireless transceiver (denoteda built-in MS above) having similar functionality to an MS, thefollowing advantages are provided:

(2.1) Assuming that the co-located base station capabilities and thestationary transceiver of an LBS are such that the base stationcapabilities and the stationary transceiver communicate with oneanother, the stationary transceiver can be signaled by anothercomponent(s) to activate or deactivate its associated base stationcapability, thereby conserving power for the LBS that operate on arestricted power such as solar electrical power;(2.2) The stationary transceiver of an LBS can be used for transferringtarget MS location information obtained by the LBS to a conventionaltelephony base station;(2.3) Since the location of each LBS is known and can be used inlocation processing, signals therefrom may be used to (re)train wirelesslocation capabilities disclosed herein. That is, by activating each LBSstationary transceiver so that there is signal communication between thestationary transceiver and surrounding base stations within range,wireless signal characteristic values for the location of the stationarytransceiver are obtained for each such base station. Accordingly, suchcharacteristic values can then be associated with the known location ofthe stationary transceiver for training various of the locationprocessing modules disclosed herein such as the classification FOMsdiscussed above. In particular, such training and/or calibrating mayinclude:

(i) (re)training FOMs;

(ii) adjusting the confidence value initially assigned to a locationhypothesis according to how accurate the generating FOM is in estimatingthe location of the stationary transceiver using data obtained fromwireless signal characteristics of signals between the stationarytransceiver and base stations with which the stationary transceiver iscapable of communicating;

(iii) automatically updating the previously mentioned historical database (i.e., the location signature data base), wherein the stored signalcharacteristic data for each stationary transceiver can be used fordetecting environmental and/or topographical changes (e.g., a newlybuilt high rise or other structures capable of altering the multipathcharacteristics of a given geographical area); and

(iv) tuning of the location system parameters, wherein the steps of: (a)modifying various system parameters and (b) testing the performance ofthe modified location system on verified mobile station location data(including the stationary transceiver signal characteristic data), thesesteps being interleaved and repeatedly performed for obtaining bettersystem location accuracy within useful time constraints.

Also disclosed herein is a mobile (location) base station (MBS) that canbe, for example, incorporated into a vehicle, such as an ambulance,police car, or taxi. Such a vehicle can travel to sites having atransmitting target MS, wherein such sites may be randomly located andthe signal characteristic data from the transmitting target MS at such alocation can consequently be archived with a verified locationmeasurement performed at the site by the mobile location base station.Moreover, it is important to note that such a mobile location basestation as its name implies also includes base station electronics forcommunicating with mobile stations, though not necessarily in the mannerof a conventional infrastructure base station. In particular, a mobilelocation base station may (in one embodiment) only monitor signalcharacteristics, such as MS signal strength, from a target MS withouttransmitting signals to the target MS. Alternatively, a mobile locationbase station can periodically be in bi-directional communication with atarget MS for determining a signal time-of-arrival (ortime-difference-of-arrival) measurement between the mobile location basestation and the target MS. Additionally, each such mobile location basestation includes components for estimating the location of the mobilelocation base station, such mobile location base station locationestimates being important when the mobile location base station is usedfor locating a target MS via, for example, time-of-arrival ortime-difference-of-arrival measurements as one skilled in the art willappreciate. In particular, a mobile location base station can include:

(3.1) a mobile station (MS) for both communicating with other componentsof the wireless location capabilities disclosed herein (such as alocation processing center);(3.2) a GPS receiver for determining a location of the mobile locationbase station;(3.3) a gyroscope and other dead reckoning devices; and(3.4) devices for operator manual entry of a mobile location basestation location.

Furthermore, a mobile location base station includes modules forintegrating or reconciling distinct mobile location base stationlocation estimates that, for example, can be obtained using thecomponents and devices of (3.1) through (3.4) above. That is, locationestimates for the mobile location base station may be obtained from: GPSsatellite data, mobile location base station data provided by thelocation processing center, dead reckoning data obtained from the mobilelocation base station vehicle dead reckoning devices, and location datamanually input by an operator of the mobile location base station.

Location estimating system embodiments disclosed herein offer manyadvantages over existing location systems. Such embodiments may employ anumber of distinctly different location estimators which provide agreater degree of accuracy and/or reliability than is possible withexisting wireless location systems. For instance, the location modelsprovided may include not only the radius-radius/TOA and TDOA techniquesbut also adaptive techniques such as artificial neural net techniquesand the techniques disclosed in the U.S. Pat. No. 6,026,304 byHilsenrath et. al. incorporated by reference herein, and angle ordirection of arrival techniques as well as substantially any otherwireless location technique wherein appropriate input data can beobtained. Note that hybrid location estimators based on combinations ofsuch techniques (such as the location technique of U.S. Pat. No.5,987,329 by Yost et. al). may also be provided.

Various location estimating system embodiments disclosed herein mayprovide various strategies for activating, within a single MS locationinstance, one or more location estimators (FOMs), wherein each suchactivated location estimator is provided with sufficient wireless signaldata input for the activation. In one embodiment, one such strategy maybe called “greedy” in that substantially as many location estimators maybe activated as there is sufficient input (additionally, time andresources as well) for activation. Note that some wireless locationtechniques are dependent on specialized location related devices beingoperational such as fixed or network based receivers, antennas,tranceivers, and/or signal processing equipment. Additionally note thatsome location techniques also require particular functionality to beoperable in the MS; e.g., functionality for detecting one or morelocation related signals from satellites (more generally non-terrestrialtransmitting stations). For example, the signals may be GPS signals.Accordingly, certain wireless location techniques may have theiractivations dependent upon whether such location related devices and/orMS functionality are available and operable for each instance ofdetermining an MS location. Thus, for each MS wireless locationinstance, location estimators may be activated according to the operablefeatures present during an MS location instance for providing inputactivation data.

Various location estimating system embodiments disclosed herein may beable to adapt to environmental changes substantially as frequently asdesired. Thus, such embodiments may be able to take into account changesin the location topography over time without extensive manual datamanipulation. Moreover, the wireless location capabilities disclosedherein can be utilized with varying amounts of signal measurementinputs. Thus, if a location estimate is desired in a very short timeinterval (e.g., less than approximately one to two seconds), then thewireless location capabilities disclosed herein can be used with only asmuch signal measurement data as is possible to acquire during an initialportion of this time interval. Subsequently, after a greater amount ofsignal measurement data has been acquired, additional more accuratelocation estimates may be obtained. Note that this capability can beuseful in the context of 911 emergency response in that a first quickcoarse wireless mobile station location estimate can be used to route a911 call from the mobile station to a 911 emergency response center thathas responsibility for the area containing the mobile station and the911 caller. Subsequently, once the 911 call has been routed according tothis first quick location estimate, by continuing to receive additionalwireless signal measurements, more reliable and accurate locationestimates of the mobile station can be obtained.

Various location estimating system embodiments disclosed hereindemonstrate the utilization of various novel computational paradigmssuch as:

(4.1) providing a multiple FOM computational architecture (asillustrated in FIG. 8) wherein:

-   -   (4.1.1) the hypotheses may be generated by modular independent        hypothesizing computational models (FOMs), wherein the FOMs have        been calibrated to thereby output confidence values        (probabilities) related to the likelihood of correspondingly        generated hypotheses being correct;    -   (4.1.2) the location hypotheses from the FOMs may be further        processed using additional amounts of application specific        processing common or generic to a plurality of the FOMs;    -   (4.1.3) the computational architecture may enhance the        hypotheses generated by the FOMs both according to past        performance of the models and according to application specific        constraints and heuristics without requiring complex feedback        loops for recalibrating one or more of the FOMs;    -   (4.1.4) the FOMs are relatively easily integrated into, modified        and extracted from the computational architecture;        (4.2) providing a computational paradigm for enhancing an        initial estimated solution to a problem by using this initial        estimated solution as, effectively, a query or index into an        historical data base of previous solution estimates and        corresponding actual solutions for deriving an enhanced solution        estimate based on past performance of the module that generated        the initial estimated solution.

Additionally, the wireless location systems and applications therefordisclosed herein need not have their computational moduled co-located.In particular, various modules can be remotely located from one anotherand communicate with one another via telecommunication transmissionssuch as telephony technologies and/or the Internet. For example, somenumber of the first order models may reside in remote locations andcommunicate their generated hypotheses via the Internet.

The processing following the generation of location hypotheses (eachhaving an initial location estimate) by the first order models may besuch that this processing can be provided on Internet user nodes and thefirst order models may reside at Internet server sites. In thisconfiguration, an Internet user may request hypotheses from such remotefirst order models and perform the remaining processing at his/her node.

Additionally, there may be one or more central location developmentsites that may be networked to, for example, geographically dispersedlocation centers providing location services, wherein the FOMs may beaccessed, substituted, enhanced or removed dynamically via networkconnections (via, e.g., the Internet) with a central locationdevelopment site. Thus, a small but rapidly growing municipality insubstantially flat low density area might initially be provided withaccess to, for example, two or three FOMs for generating locationhypotheses in the municipality's relatively uncluttered radio signalingenvironment. However, as the population density increases and the radiosignaling environment becomes cluttered by, for example, thermal noiseand multipath, additional or alternative FOMs may be transferred via thenetwork to the location center for the municipality.

Note that there may be (but not necessarily) a lack of sequencingbetween the FOMs and subsequent processing of hypotheses (e.g., locationhypotheses, or other application specific hypotheses), the FOMs can beincorporated into an expert system, if desired. For example, each FOMmay be activated from an antecedent of an expert system rule. Thus, theantecedent for such a rule can evaluate to TRUE if the FOM outputs alocation hypothesis, and the consequent portion of such a rule may putthe output location hypothesis on a list of location hypothesesoccurring in a particular time window for subsequent processing by thelocation center. Alternatively, activation of the FOMs may be in theconsequents of such expert system rules. That is, the antecedent of suchan expert system rule may determine if the conditions are appropriatefor invoking the FOM(s) in the rule's consequent.

A blackboard system with intelligent agents (FOMs) may be used todetermine a MS geographical location. In such an embodiment, each of theintelligent agents is calibrated using archived data so that for each ofthe input data sets provided either directly to the intelligent agentsor to the blackboard, each hypothesis generated and placed on theblackboard by the intelligent agents has a corresponding confidencevalue indicative of an expected validity of the hypothesis.

Further features and advantages of the present disclosure are providedby the figures and detailed description accompanying this summary.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates various perspectives of radio propagationopportunities which may be considered in addressing correlation withmobile to base station ranging.

FIG. 2 shows aspects of the two-ray radio propagation model and theeffects of urban clutter.

FIG. 3 provides a typical example of how the statistical power budget iscalculated in design of a Commercial Mobile Radio Service Providernetwork.

FIG. 4 illustrates an overall view of a wireless radio location networkarchitecture, based on advanced intelligent network (AIN) principles.

FIG. 5 is a high level block diagram of an embodiment of the wirelesslocation capabilities disclosed herein for locating a mobile station(MS) within a radio coverage area.

FIG. 6 is a high level block diagram of the location center 142.

FIG. 7 is a high level block diagram of the hypothesis evaluator for thelocation center.

FIG. 8 is a substantially comprehensive high level block diagramillustrating data and control flows between the components of (and/oraccessed by) the location center/gateway 142, as well the functionalityof these components.

FIGS. 9A and 9B are a high level data structure diagram describing thefields of a location hypothesis object generated by the first ordermodels 1224 of the location center.

FIG. 10 is a graphical illustration of the computation performed by themost likelihood estimator 1344 of the hypothesis evaluator.

FIG. 11 is a high level block diagram of the mobile base station (MBS).

FIG. 12 is a high level state transition diagram describingcomputational states the Mobile Base station enters during operation.

FIG. 13 is a high level diagram illustrating the data structuralorganization of the Mobile Base station capability for autonomouslydetermining a most likely MBS location from a plurality of potentiallyconflicting MBS location estimating sources.

FIG. 14 illustrates the primary components of the signal processingsubsystem.

FIG. 15 illustrates how automatic provisioning of mobile stationinformation from multiple CMRS occurs.

FIG. 16 illustrates another embodiment of the location engine 139,wherein the context adjuster 1326 (denoted in this figure as “locationhypothesis adjuster modules”) includes a module (1436) that is capableof adjusting location hypotheses for reliability, and another module(1440) that is capable of adjusting location hypotheses for accuracy.

FIG. 17 illustrates the primary components of the signal processingsubsystem.

FIG. 18 is a block diagram further illustrating a wireless locationgateway.

FIG. 19 is a block diagram of an electronic networked yellow pages forproviding intelligent advertising services, wherein wireless locationservices may be utilized.

FIG. 20 is a high level block diagram illustrating the wirelessapplication platform of the present disclosure.

FIG. 21 is a more detailed block diagram illustrating the wirelessapplication platform of the present disclosure.

FIG. 22 is a high level flowchart of the operation of the wirelessapplication platform of the present disclosure.

FIGS. 23A and 23B show a flowchart of the steps performed for routing auser along a route that includes a plurality of locations where the usercan access a desired item (product or service) at each of the pluralityof locations.

FIGS. 24A and 24B show a flowchart that is illustrative of the stepsperformed when, e.g., MS user input of preferences and needs isiteratively examined at various user locations for determining thelocation(s) that sufficiently satisfy user specified constraints (e.g.,temporal or situational constraints) so that the user is alerted ornotified of products and/or services that satisfy the user's input. Thesteps 2004 through 2040 are fully disclosed and explained in thesections hereinabove.

DETAILED DESCRIPTION

In order to simplify the description herein the following U.S. patentsand U.S. patent applications (a) through (l) are fully incorporated byreference:

-   -   (a) U.S. patent application Ser. No. 12/861,817 filed Aug. 23,        2010.    -   (b) U.S. patent application Ser. No. 12/021,222 filed Jan. 28,        2008 and having U.S. Patent Application Publication No. US        2008-0133126 A1    -   (c) U.S. patent application Ser. No. 11/838,213 filed Aug. 13,        2007 having U.S. Patent Application Publication No. US        2007-0287473 A1.    -   (d) U.S. patent application Ser. No. 11/739,097 filed Apr. 24,        2007 having U.S. Patent Application Publication No. US        2008-0167049 A1.    -   (e) U.S. patent application Ser. No. 11/464,880 filed Aug. 16,        2006 having U.S. Patent Application Publication No. US        2006-0276201 A1.    -   (f) U.S. patent application Ser. No. 10/297,449 filed Dec. 6,        2002 (now U.S. Pat. No. 7,714,778).    -   (g) U.S. patent application Ser. No. 10/262,413 filed Sep. 30,        2002 (now U.S. Pat. No. 7,298,327).    -   (h) U.S. patent application Ser. No. 09/820,584 filed Mar. 28,        2001 (now U.S. Pat. No. 6,952,181).    -   (i) U.S. patent application Ser. No. 09/770,838 filed Jan. 26,        2001 (now U.S. Pat. No. 7,525,484).    -   (j) U.S. patent application Ser. No. 09/299,115 filed Apr. 23,        1999 (now U.S. Pat. No. 6,249,252).    -   (k) U.S. patent application Ser. No. 09/230,109 filed Jul. 8,        1999 (now U.S. Pat. No. 6,236,365).    -   (l) U.S. patent application Ser. No. 09/176,587 filed Oct. 21,        1998 (now U.S. Pat. No. 7,274,332).

FIG. 4 is a high level diagram of one embodiment of a wirelessradiolocation architecture for the wireless location capabilitiesdisclosed herein. Accordingly, this figure illustrates theinterconnections between the components of a wireless cellularcommunication network, such as, a typical PCS network configuration andvarious components. In particular, as one skilled in the art willunderstand, a typical wireless (PCS) network includes:

-   -   (a) a (large) plurality of wireless mobile stations (MSs) 140        for at least one of voice related communication, visual (e.g.,        text such as is provided by a short message service) related        communication, and location related communication. Note that        some of the MSs 140 may include the electronics and        corresponding software to detect and process signals from        non-terrestrial transmission stations such as GPS and/or GLONASS        satellites. Moreover, note that such non-terrestrial        transmission stations can also be high attitude aircraft which,        e.g., can hover over a metropolitan area thereby facilitating        wireless communications;    -   (b) a mobile switching center (MSC) 112;    -   (c) a plurality of wireless cell sites in a radio coverage area        120, wherein each cell site includes an infrastructure base        station such as those labeled 122 (or variations thereof such as        122A-122D). In particular, the base stations 122 denote the        standard high traffic, fixed location base stations used for        voice and data communication with a plurality of MSs 140, and,        also used for communication of information related to locating        such MSs 140. Additionally, note that the base stations labeled        152 are more directly related to wireless location enablement.        For example, as described in greater detail hereinbelow, the        base stations 152 may be low cost, low functionality        transponders that are used primarily in communicating MS        location related information to the location center 142 (via        base stations 122 and the MSC 112). Note that unless stated        otherwise, the base stations 152 will be referred to hereinafter        as location base station(s) 152 or simply LBS(s) 152;    -   (d) a public switched telephone network (PSTN) 124 (which may        include signaling system links 106 having network control        components such as: a service control point (SCP) 104, one or        more signaling transfer points (STPs) 110.

In addition, the wireless location capabilities disclosed hereinprovides one or more location centers/gateways 142. Such gateways may bedescribed at a high level as follows.

Location Center/Gateway 142 Description

A location center/gateway 142, (also be referred to as a locationcenter/gateway, or simply gateway), in response to a location requestreceived at the location center, can request activation of one or moreof a plurality of wireless location techniques in order to locate an MS140.

Various embodiments are provided herein of the location center/gateway142. In particular, FIG. 18 is block diagram illustrating anotherembodiment of the location center/gateway 142. Note that the wirelesslocation gateway activation requests may be dependent upon, e.g.,

-   -   (a) a wireless network with which the MS 140 may be in contact,        such a network may be:        -   (i) a commercial mobile radio network supporting telephony            functionality,        -   (ii) a short messaging service or paging network;        -   (iii) a wireless network of beacons for providing location            related information such as GPS and LORAN C,        -   (iv) wireless carrier independent networks for performing            wireless location such as the wireless location network            provided by Times Three, Suite #220, Franklin Atrium, 3015            5th Avenue N.E. Calgary, AB T2A 6TB,        -   (v) a wireless broadcasting network for use in activating an            MS 140 of, e.g., a stolen vehicle such as is provided by            LoJack Corporation, 333 μm Street, Dedham, Mass. 02026,            and/or        -   (vi) a hybrid network including portions of wireless            networks each network providing different types of signal            measurements for performing wireless location);    -   (b) the location signal measurement obtaining capabilities of        the wireless network with which the MS may be in contact. For        example, such a network may only support a network centric        location technique;    -   (c) the functionality of the MS 140 such as: the type(s) of        wireless signals which can be detected and processed by the MS        such as:        -   (i) non-terrestrial signals such as GPS signals,        -   (ii) signals from wireless beaconing/broadcasting systems            such as for LORAN C signals or stolen vehicle broadcast            networks for activating an MS 140 attached to the stolen            vehicle, or        -   (iii) wireless telephony protocols like CDMA, TDMA, and/or            GSM,    -   (d) a likely location of the target MS 140. For example, if the        target MS 140 is likely to be in Japan rather than the United        States, then the location service provider contacted by the        gateway 142 may be different from the location service provider        if the MS is likely to be in the U.S.

Moreover, regarding the plurality of wireless location techniques(embodiments thereof also denoted herein as “location estimators”) forwhich activation may be requested by the gateway, these techniques maybe co-located with the gateway, accessible via a network including: (i)local area networks, and (ii) wide area networks such as a telephony(wired or wireless) network, the Internet or a cable network. Thegateway 142 may supply to one or more of the location estimators,measurements of communications between the MS 140 and one or morenetworks for determining a location of the MS 140. Alternatively,instead of supplying such measurements (locally or remotely, and, via anetwork or otherwise), the gateway 142 may provide, with the locationactivation request, an identification of where the measurements may beobtained (e.g., one or more network addresses). In yet anotheralternative, such a gateway 142 may also send request(s) to thenetwork(s) having such MS communication measurements to forward them toparticular location estimators. Note, that in performing these tasks,the gateway 142 may receive with a location request (or may retrieve inresponse thereto) information regarding the functionality of the targetMS 140, e.g., as discussed above. Accordingly, such information may beused in selecting the location estimator to which an activation requestis provided. Thus, the gateway 142 may be the intermediary betweenlocation requesting applications and the location estimators, therebyproviding a simple, uniform application programming interface (API) forsuch applications substantially independently of the location estimatorsthat are activated to fulfill such location requests. Moreover, thegateway 142 (or embodiments thereof) can substantially ease the burdenon geolocation service providers by providing a substantially uniformmethod for obtaining target MS/network signal data for use in locatingthe target MS. Thus, by interfacing to the gateway 142, a locationservice provider may substantially reduce the number and complexity ofits data exchange interfaces with the wireless networks for obtainingtarget MS/network signal data. Similarly, the networks capturing suchsignal data may also reduce the complexity and number of theirinterfaces for providing such signal data to location service providers.Additionally, note that the gateway may also fulfill location requestswherein the location is for a stationary and/or wireline handset insteadof a mobile station 140. Accordingly, the gateway 142 may request accessto, e.g., phone location information stored in a carrier's database ofpremise provisioning equipment as one skilled in the art willunderstand. In some embodiments of the gateway 142, it may alsofacilitate in the providing of certain location related services inaddition to providing, e.g., MS 140 locations. In particular, one ormore of the following location related services may be facilitated bythe gateway 142 or may be made operative via the wireless locationcapabilities of the gateway 142. However, note that the followinglocation related services can, in general, be provided without use of agateway 142, albeit, e.g., in a likely more restricted context whereinnot all available wireless location estimating techniques are utilized,and/or by multiplying the number of interfaces to geolocation serviceproviders (e.g., distinct wireless location interfaces provided directlyto each wireless location service provider utilized). Further note thatat some of these applications are described in greater detail in latersections herein:

-   -   (10.1) Routing instructions for directing a vehicle or person to        get to a desired destination. Note, that there are various forms        of utilizing MS location capabilities to determine an        appropriate route, and related teachings are provided in        copending U.S. patent application titled, “Wireless Location        Using A Plurality of Commercial Network Infrastructures,”        by F. W. LeBlanc, Dupray and Karr filed Jan. 22, 1999 and having        U.S. Pat. No. 6,236,365 issued May 22, 2001 which is fully        incorporated herein by reference, and by the following two        copending U.S. patent applications which are also incorporated        herein by reference: (i) “Location Of A Mobile Station” filed        Nov. 24, 1999 having application Ser. No. 09/194,367 whose        inventors are Dupray and Karr, and (ii) “A Wireless Location        System For Calibrating Multiple Location Estimators” filed Oct.        21, 1998 having application Ser. No. 09/176,587 whose inventor        is Dupray. Additionally, other routing services may also be        provided by the gateway 142 (or by service providers in        cooperation with the gateway). For example, the gateway 142 may        cooperate with an automated speech recognition interpretation        and synthesis unit for providing substantially automated        interactive communication with an MS 140 for providing spoken        directions. Note that such directions may be provided in terms        of street names and/or descriptions of the terrain (e.g., “the        glass high rise on the left having pink tinted glass”).    -   (10.2) Advertising may be directed to an MS 140 according to its        location. In at least some studies it appears that MS 140 users        do not respond well to unsolicited wireless advertisement        whether location based or otherwise. However, in response to        certain user queries for locally available merchandise, certain        advertisements may be viewed in a more friendly light. Thus, by        allowing an MS user to contact, e.g., a wireless advertising        portal by voice or via wireless Internet, and describe certain        merchandise desired (e.g., via interacting with an automated        speech interaction unit) the user may be able to describe and        receive (at his/her MS 140) visual displays of merchandise that        may satisfy such a user's request. For example, an MS user may        provide a spoken request such as: “I need a shirt, who has        specials near here?”.    -   (10.3) Applications that combine routing with safety for        assisting MS users with requests such as “How do I get back to        the hotel safely?”;    -   (10.4) Applications that combine routing with sight seeing        and/or guided tour capabilities where routing is interactive and        dependent on feedback from users regarding, e.g., user        interests;    -   (10.5) Applications using Internet picture capture with real        time voice capture and MS location (e.g., sightseeing, security,        and law enforcement),    -   (10.6) Intelligent transportation (e.g., voice commanded        vehicles);    -   (10.7) Applications that monitor whether or not a person or        object (e.g., a vehicle) is within a predetermined boundary.        Note, that such an application may automatically provide speech        output to the MS user (or other authorized user) when the person        or object is beyond the predetermined boundary;    -   (10.8) Applications that route to an event and automatically        determine parking availability and where to park; and    -   (10.9) Traffic/weather condition routing.

Further note that various architectures for the location center/locationgateway are within the scope of the wireless location capabilitiesdisclosed herein including a distributed architecture wherein inaddition to the FOMs being possibly remotely accessed (e.g., via acommunications network such as the Internet), the gateway itself may bedistributed throughout one or more communication networks. Thus, alocation request received at a first location gateway portion may berouted to a second location gateway portion (e.g., via the Internet).Such a distributed gateway may be considered a “meta-gateway” and infact such gateway portions may be fully functioning gateways in theirown right. Thus, such routing therebetween may be due to contractualarrangements between the two gateways (each fulfilling location requestsfor a different network, wireless carrier, and/or geographical region).For example, for locating a stolen vehicle, it is not uncommon for thestolen vehicle to be transported rapidly beyond the coverage area of alocal or regional wireless vehicle locating service. Moreover, a givenlocation gateway may provide location information for only certain areascorresponding, e.g., to contractual arrangements with the wirelesscarriers with which the location gateway is affiliated. Thus, a firstlocation gateway may provide vehicle locations for a first collection ofone or more wireless networks, and a second location gateway may providevehicle locations for a second collection of one or more wirelessnetworks. Accordingly, for an MS 140 built into a vehicle which can bedetected by one or more wireless networks (or portions thereof) in eachof the first and second collections, then if the vehicle is stolen, thefirst gateway may be initially contacted for determining whether thevehicle can be located via communications with the first collection ofone or more wireless networks, and if the vehicle can not be located,the first gateway may provide a location request to the second gatewayfor thereby locating the stolen vehicle via wireless communications withone or more wireless networks of the second collection. Furthermore, thefirst gateway may provide location requests for the stolen vehicle toother location gateways.

The wireless location capabilities disclosed herein provides thefollowing additional components:

-   (11.1) one or more mobile base stations 148 (MBS) which are    optional, for physically traveling toward the target MS 140 or    tracking the target MS;-   (11.2) a plurality of location base stations 152 (LBS) which are    optional, distributed within the radio coverage areas 120, each LBS    152 having a relatively small MS 140 detection area 154. Note that    such LBSs 152 may also support Internet and/or TCP/IP transmissions    for transmitting visual location related information (e.g.,    graphical, or pictorial) related to an MS location request.

Since location base stations 152 can be located on, e.g., each floor ofa multi-story building, the wireless location technology describedherein can be used to perform location in terms of height as well as bylatitude and longitude.

In operation, an MS 140 may utilize one or more of the wirelesstechnologies, CDMA, TDMA, AMPS, NAMPS or GSM for wireless communicationwith: (a) one or more infrastructure base stations 122, (b) mobile basestation(s) 148, or (c) an LBS 152. Additionally, note that in someembodiments of the wireless location capabilities disclosed herein,there may be MS to MS communication.

Referring to FIG. 4 again, additional detail is provided of typical basestation coverage areas, sectorization, and high level components withina radio coverage area 120, including the MSC 112. Three exemplary basestations (BSs) are 122A, 122B and 122C, each of which radiatereferencing signals within their area of coverage 169 to facilitatemobile station (MS) 140 radio frequency connectivity, and various timingand synchronization functions. Note that some base stations may containno sectors 130 (e.g. 122E), thus radiating and receiving signals in a360 degree omnidirectional coverage area pattern, or the base stationmay contain “smart antennas” which have specialized coverage areapatterns. However, the generally most frequent base stations 122 havethree sector 130 coverage area patterns. For example, base station 122Aincludes sectors 130, additionally labeled a, b and c. Accordingly, eachof the sectors 130 radiate and receive signals in an approximate 120degree arc, from an overhead view. As one skilled in the art willunderstand, actual base station coverage areas 169 (stylisticallyrepresented by hexagons about the base stations 122) generally aredesigned to overlap to some extent, thus ensuring seamless coverage in ageographical area. Control electronics within each base station 122 areused to communicate with a mobile stations 140. Information regardingthe coverage area for each sector 130, such as its range, area, and“holes” or areas of no coverage (within the radio coverage area 120),may be known and used by the location center 142 to facilitate locationdetermination. Further, during communication with a mobile station 140,the identification of each base station 122 communicating with the MS140 as well, as any sector identification information, may be known andprovided to the location center 142.

In the case of the base station types 122, 148, and 152 communicatinglocation information, a base station or mobility controller 174 (BSC)controls, processes and provides an interface between originating andterminating telephone calls from/to mobile station (MS) 140, and themobile switch center (MSC) 112. The MSC 122, on-the-other-hand, performsvarious administration functions such as mobile station 140registration, authentication and the relaying of various systemparameters, as one skilled in the art will understand.

The base stations 122 may be coupled by various transport facilities 176such as leased lines, frame relay, T-Carrier links, optical fiber linksor by microwave communication links.

When an MS 140 is powered on and in the idle state, it constantlymonitors the pilot signal transmissions from each of the base stations122 located at nearby cell sites. Since base station/sector coverageareas may often overlap, such overlapping enables an MS 140 to detect,and, in the case of certain wireless technologies, communicatesimultaneously along both the forward and reverse paths, with multiplebase stations 122 and/or sectors 130. In FIG. 4, the constantlyradiating pilot signals from base station sectors 130, such as sectorsa, b and c of BS 122A, are detectable by MSs 140 within the coveragearea 169 for BS 122A. That is, the mobile stations 140 scan for pilotchannels, corresponding to a given base station/sector identifiers(IDs), for determining in which coverage area 169 (i.e., cell) it iscontained. This is performed by comparing signal strengths of pilotsignals transmitted from these particular cell-sites.

The mobile station 140 then initiates a registration request with theMSC 112, via the base station controller 174. The MSC 112 determineswhether or not the mobile station 140 is allowed to proceed with theregistration process (except, e.g., in the case of a 911 call, whereinno registration process is required). Once any required registration iscomplete, calls may be originated from the mobile station 140 or callsor short message service messages can be received from the network. Notethat the MSC 112 communicates as appropriate, with a class 4/5 wirelinetelephony circuit switch or other central offices, connected to the PSTN124 network. Such central offices connect to wireline terminals, such astelephones, or any communication device compatible with a wireline. ThePSTN 124 may also provide connections to long distance networks andother networks.

The MSC 112 may also utilize IS/41 data circuits or trunks connecting tosignal transfer point 110, which in turn connects to a service controlpoint 104, via Signaling System #7 (SS7) signaling links (e.g., trunks)for intelligent call processing, as one skilled in the art willunderstand. In the case of wireless AIN services such links are used forcall routing instructions of calls interacting with the MSC 112 or anyswitch capable of providing service switching point functions, and thepublic switched telephone network (PSTN) 124, with possible terminationback to the wireless network.

Referring still to FIG. 4, the location center/gateway (LC) 142interfaces with the MSC 112 either via dedicated transport facilities178, using, e.g., any number of LAN/WAN technologies, such as Ethernet,fast Ethernet, frame relay, virtual private networks, etc., or via thePSTN 124. The gateway 142 may receive autonomous (e.g., unsolicited)command/response messages regarding, for example: (a) the state of thewireless network of each commercial radio service provider utilizing theLC 142 for wireless location services, (b) MS 140 and BS 122 radiofrequency (RF) measurements, (c) communications with any MBSs 148, and(d) location applications requesting MS locations using the locationcenter/gateway 142. Conversely, the LC 142 may provide data and controlinformation to each of the above components in (a)-(d). Additionally,the LC 142 may provide location information to an MS 140, via a BS 122.Moreover, in the case of the use of a mobile base station (MBS) 148,several communications paths may exist with the LC 142.

The MBS 148 may act as a low cost, partially-functional, moving basestation, and is, in one embodiment, situated in a vehicle (e.g., land,water or aircraft) where an operator may engage in MS 140 searching andtracking activities. In providing these activities using CDMA, the MBS148 provides a forward link pilot channel for a target MS 140, andsubsequently receives unique BS pilot strength measurements from the MS140. The MBS 148 also includes a mobile station 140 for datacommunication with the gateway 142, via a BS 122. In particular, suchdata communication includes telemetering at least the geographicposition (or estimates thereof) of the MBS 148, various RF measurementsrelated to signals received from the target MS 140, and in someembodiments, MBS 148 estimates of the location of the target MS 140. Insome embodiments, the MBS 148 may utilize multiple-beam fixed antennaarray elements and/or a moveable narrow beam antenna, such as amicrowave dish 182. The antennas for such embodiments may have a knownorientation in order to further deduce a radio location of the target MS140 with respect to an estimated current location of the MBS 148. Aswill be described in more detail herein below, the MBS 148 may furthercontain a satellite (e.g., global positioning system (GPS)) receiver (orother receiver for non-terrestrial wireless signals) for determining thelocation of the MBS 148 and/or providing wireless location assistance atarget MS 140, e.g., providing GPS information to the MS to assist theMS in determining its location. Additionally, the MBS 148 may includedistance sensors, dead-reckoning electronics, as well as an on-boardcomputing system and display devices for locating both the MBS 148itself as well as tracking and locating the target MS 140. The computingand display provides a means for communicating the position of thetarget MS 140 on a map display to an operator of the MBS 148. It isimportant to note that in one embodiment, an MBS 148 may determine itslocation substantially independent of the communications network(s) withwhich the MBS communicates.

Each location base station (LBS) 152 is a low cost location device. Insome embodiments, to provide such LBS's cost effectively, each LBS 152only partially or minimally supports the air-interface standards of theone or more wireless technologies used in communicating with both theBSs 122 and the MSs 140. Each LBS 152, when put in service, is placed ata fixed location, such as at a traffic signal, lamp post, etc., whereinthe location of the LBS may be determined as accurately as, for example,the accuracy of the locations of the infrastructure BSs 122. Assumingthe wireless technology, CDMA, is used, each BS 122 uses a time offsetof the pilot PN sequence to identify a forward CDMA pilot channel. Inone embodiment, each LBS 152 emits a unique, time-offset pilot PNsequence channel in accordance with the CDMA standard in the RF spectrumdesignated for BSs 122, such that the channel does not interfere withneighboring BSs 122 cell site channels, and does not interfere withneighboring LBSs 152. Each LBS 152 may also contain multiple wirelessreceivers in order to monitor transmissions from a target MS 140.Additionally, each LBS 152 contains mobile station 140 electronics,thereby allowing the LBS to both be controlled by, e.g., the gateway 142or the wireless carrier(s) for the LBS, and to transmit information to,e.g., the gateway 142 (via, e.g., at least one neighboring BS 122), orto another wireless location service provider such as one providing oneor more FOMs.

As mentioned above, when the location of a particular target MS 140 isdesired, the gateway 142 may request location information about thetarget MS 140 from, for instance, one or more activated LBSs 152 in ageographical area of interest. Accordingly, whenever the target MS 140is in an LBS coverage area, or is suspected of being in the coveragearea, either upon command from the gateway 142 (or other locationservice provider), or in a substantially continuous (or periodic)fashion, the LBS's pilot channel appears to the target MS 140 as apotential neighboring base station channel, and consequently, is placed,for example, in the CDMA neighboring set, or the CDMA remaining set ofthe target MS 140 (as one familiar with the CDMA standards willunderstand).

During the normal CDMA pilot search sequence of the mobile stationinitialization state (in the target MS), the target MS 140 will, ifwithin range of such an activated LBS 152, detect the LBS pilot presenceduring the CDMA pilot channel acquisition substate. Consequently, thetarget MS 140 performs RF measurements on the signal from each detectedLBS 152. Similarly, an activated LBS 152 can perform RF measurements onthe wireless signals from the target MS 140. Accordingly, each LBS 152detecting the target MS 140 may subsequently telemeter back to the LC142 measurement results related to signals from/to the target MS 140.Moreover, upon command, the target MS 140 may telemeter back to thegateway 142 its own measurements of the detected LBSs 152, andconsequently, this new location information, in conjunction withlocation related information received from the BSs 122, can be used tolocate the target MS 140.

It should be noted that an LBS 152 will normally deny hand-off requests,since typically the LBS does not require the added complexity ofhandling voice or traffic bearer channels, although economics and peaktraffic load conditions may dictate preference here. Note that GPStiming information, needed by any CDMA base station, is either achievedvia a the inclusion of a local GPS receiver or via a telemetry processfrom a neighboring conventional BS 122, which contains a GPS receiverand timing information. Since energy requirements are minimal in such anLBS 152, (rechargeable) batteries or solar cells may be used to powerthe LBSs. Further, no expensive terrestrial transport link is typicallyrequired since two-way communication is provided by an included MS 140(or an electronic variation thereof) within each LBS. Thus, LBSs 152 maybe placed in numerous locations, such as:

-   -   (a) in dense urban canyon areas (e.g., where signal reception        may be poor and/or very noisy);    -   (b) in remote areas (e.g., hiking, camping and skiing areas);    -   (c) along highways (e.g., for emergency as well as monitoring        traffic flow), and their rest stations; or    -   (d) in general, wherever more location precision is required        than is obtainable using other wireless infrastructure network        components.

Location Center—Network Elements API Description

A location application programming interface 136 (FIG. 4), denotedL-API, is may be provided between the location center/gateway 142 (LC)and the mobile switch center (MSC) network element type, in order tosend and receive various control, signals and data messages. The L-APImay be implemented using a preferably high-capacity physical layercommunications interface, such as IEEE standard 802.3 (10 baseTEthernet), although other physical layer interfaces could be used, suchas fiber optic ATM, frame relay, etc. At least two forms of L-APIimplementation are possible. In a first case, the signal control anddata messages are provided using the MSC 112 vendor's native operationsmessages inherent in the product offering, without any specialmodifications. In a second case, the L-API includes a full suite ofcommands and messaging content specifically optimized for wirelesslocation purposes, which may require some, although minor development onthe part of an MSC vendor.

Signal Processor Description

Referring to FIG. 17, a signal processing subsystem (labeled 1220 inother figures) may be provided (or accessed) by the gateway 142. Such asignal processing subsystem may: (a) receive control messages and signalmeasurements from one or more wireless service provider networks, and(b) transmit appropriate control messages to such wireless networks viathe location applications programming interface 136 referenced earlier,for wireless location purposes. The signal processing subsystem 1220additionally provides various signal identification, conditioning andpre-processing functions, including buffering, signal typeclassification, signal filtering, message control and routing functionsto the location estimating modules or FOMs.

There can be several combinations of Delay Spread/Signal Strength setsof measurements made available to the signal processing subsystem 1220.In some cases a mobile station 140 (FIG. 1) may be able to detect up tothree or four pilot channels representing three to four base stations,or as few as one pilot channel, depending upon the environment andwireless network configuration. Similarly, possibly more than one BS 122can detect a mobile station 140 transmitter signal, and the fact thatmultiple CMRS' base station equipment commonly will overlap coverageareas.

For each mobile station 140 or BS 122 transmitted signal that isdetected by a receiver group at a base or mobile station, respectively,multiple delayed signals, or “fingers” may be detected (e.g., in CDMA)and tracked resulting from multipath radio propagation conditions from agiven transmitter. In typical spread spectrum diversity CDMA receiverdesign, the “first” finger represents the most direct, or least delayedmultipath signal. Second or possibly third or fourth fingers may also bedetected and tracked, assuming the detecting base station and/or mobilestation 140 contains a sufficient number of data receivers for doing so.The signal processing subsystem may utilize various wireless signalmeasurements of transmissions between a target mobile station 140 and anetwork of base stations 122, 152 and/or 148. Such measurements can beimportant in effectively estimating the location of mobile stations 140in that it is well known that measurements of wireless signalpropagation characteristics, such as signal strength (e.g., RSSI), timedelay, angle of arrival, and any number other measurements, canindividually lead to gross errors in MS 140 location estimates.

Accordingly, one aspect of the wireless location capabilities disclosedherein is directed to utilizing a larger number of wireless signalmeasurements, and utilizing a plurality of MS 140 estimation techniquesto compensate for location estimation errors generated by some suchtechniques. For example, due to the large capital outlay costsassociated with providing three or more overlapping base stationcoverage signals in every possible location, most practical digital PCSdeployments result in fewer than three base station pilot channels beingreportable in the majority of location areas, thus resulting in alarger, more amorphous location estimates by terrestrial triangulationsystems. Thus, by utilizing wireless signal measurements from a varietyof sources substantially simultaneously and/or “greedily” (i.e., usewhatever signal measurements can be obtained from any of the signalsources as they are obtained), additional location enhancements can beobtained. For example, by enhancing a mobile station 140 withelectronics for detecting satellite transmissions (as done with mobilebase stations 148 and which also can be viewed as such an enhancedmobile station 140) additional location related signals maybe obtainedfrom:

-   -   (a) the GPS satellite system,    -   (b) the Global Navigation Satellite System (GLONASS) satellite        system, a Russian counterpart to the U.S. GPS system, and/or    -   (c) the numerous low earth orbit satellite systems (LEDs) and        medium earth orbit satellite systems (MEOs) such as the IRIDIUM        system being developed by Motorola Corp., the GLOBALSTAR system        by Loral and Qualcomm, and the ICO satellite system by ICO        Global Communications.        Thus, by combining even insufficient wireless location        measurements from different wireless communication systems,        accurate location of an MS 140 is possible. For example, by if        only two GPS satellites are detectable, but there is an        additional reliable wireless signal measurement from, e.g., a        terrestrial base station 122, then by triangulating using        wireless signal measurements derived from transmissions from        each of these three sources, a potentially reliable and accurate        MS location can be obtained.

Moreover, the transmissions from the MS 140 used for determining theMS's location need not be transmitted to terrestrial base stations(e.g., 122). It is within the scope of the wireless locationcapabilities disclosed herein that a target MS 140 may transmit locationrelated information to satellites as well. For example, if a target MS140 detects two GPS satellite transmissions and is able to subsequentlytransmit the GPS signal measurements (e.g., timing measurements) to anadditional satellite capable of determining additional MS locationmeasurements according to the signals received, then by performing atriangulation process at the location center/gateway 142 (which may beco-located with the additional satellite, or at a remote terrestrialsite), a potentially reliable and accurate MS location can be obtained.Accordingly, the wireless location capabilities disclosed herein iscapable of resolving wireless location ambiguities due to a lack oflocation related information of one type by utilizing supplementallocation related information of a different type. Note that by “type” asused here it is intended to be interpreted broadly as, e.g.,

-   -   (a) a data type of location information, and/or    -   (b) communications from a particular commercial wireless system        as opposed to an alternative system, each such system having        distinct groups of known or registered MS users.

Moreover, it can be that different FOMs are provided for at least somewireless location computational models utilizing different types oflocation related information. For example, in certain contexts wirelessnetworks based on different wireless signaling technologies may be usedto locate an MS 140 during the time period of a single emergency callsuch as E911. Moreover, in other contexts it may be possible for thetarget MS 140 to use one or more of a plurality of wirelesscommunication networks, possibly based on different wirelesscommunication technologies, depending on availability the of technologyin the coverage area. In particular, since so called “dual mode” or“tri-mode” mobile stations 140 are available, wherein such mobilestations are capable of wireless communication in a plurality ofwireless communication technologies, such as digital (e.g., CDMA, and/orTDMA) as well as analog or AMP/NAMPS, such mobile stations may utilize afirst (likely a default) wireless communication technology wheneverpossible, but switch to another wireless communication technology when,e.g., coverage of the first wireless technology becomes poor. Moreover,such different technologies are typically provided by different wirelessnetworks (wherein the term “network” is understood to include a networkof communication supporting nodes geographically spaced apart thatprovide a communications infrastructure having access to informationregarding subscribers to the network prior to a request to access thenetwork by the subscribers). Accordingly, the wireless locationcapabilities disclosed herein may include (or access) FOMs for providingmobile station location estimates wherein the target MS 140 communicateswith various networks using different wireless communicationtechnologies. Moreover, such FOMs may be activated according to thewireless signal measurements received from various wireless networksand/or wireless technologies supported by a target MS 140 and to whichthere is a capability of communicating measurements of such variedwireless signals to the FOM(s). Thus, in one embodiment of the wirelesslocation capabilities disclosed herein, there may be a triangulation (ortrilateration) based FOM for each of CDMA, TDMA and AMP/NAMPS which maybe singly, serially, or concurrently used for obtaining a particularlocation of an MS 140 at a particular time (e.g., for an E911 call).Thus, when locating a target MS 140, the MS may, if there is overlappingcoverage of two wireless communication technologies and the MS supportscommunications with both, repeatedly switch back and forth between thetwo thereby providing additional wireless signal measurements for use inlocating the target MS 140.

In one embodiment of the wireless location capabilities disclosedherein, wherein multiple FOMs may be activated substantiallysimultaneously (or alternatively, wherever appropriate input is receivedthat allow particular FOMs to be activated). Note that at least some ofthe FOMs may provide “inverse” estimates of where a target MS 140 is notinstead of where it is. Such inverse analysis can be very useful incombination with location estimates indicating where the target MS is inthat the accuracy of a resulting MS location estimate may besubstantially decreased in size when such inverse estimates are utilizedto rule out areas that otherwise appear to be likely possibilities forcontaining the target MS 140. Note that one embodiment of a FOM that canprovide such reverse analysis is a location computational model thatgenerates target MS location estimates based on archived knowledge ofbase station coverage areas (such an archive being the result of, e.g.,the compilation a RF coverage database—either via RF coverage areasimulations or field tests). In particular, such a model may providetarget MS location inverse estimates having a high confidence orlikelihood that that the target MS 140 is not in an area since either abase station 122 (or 152) can not detect the target MS 140, or thetarget MS can not detect a particular base station. Accordingly, theconfidences or likelihoods on such estimates may be used by diminishinga likelihood that the target MS is in an area for the estimate, oralternatively the confidence or likelihood of all areas of interestoutside of the estimate can increased.

Note that in some embodiments of the wireless location capabilitiesdisclosed herein, both measurements of forward wireless signals to atarget MS 140, and measurements of reverse wireless signals transmittedfrom the target MS to a base station can be utilized by various FOMs. Insome embodiments, the received relative signal strength (RRSS_(BS)) ofdetected nearby base station transmitter signals along the forward linkto the target mobile station can be more readily used by the locationestimate modules (FOMs) since the transmission power of the basestations 122 typically changes little during a communication with amobile station. However, the relative signal strength (RRSS_(MS)) oftarget mobile station transmissions received by the base stations on thereverse link may require more adjustment prior to location estimatemodel use, since the mobile station transmitter power level changesnearly continuously.

Location Center High Level Functionality

At a very high level the location center/gateway 142 computes (orrequests computation of) location estimates for a wireless mobilestation 140 by performing at least some of the following steps:

(23.0) receiving an MS location request;(23.1) receiving measurements of signal transmission characteristics ofcommunications communicated between the target MS 140 and one or morewireless infrastructure base stations 122. Note, this step may only beperformed if the gateway provides such measurements to a FOM (e.g, a FOMco-located therewith);(23.2) filtering the received signal transmission characteristics (by asignal processing subsystem 1220 illustrated in, e.g., FIGS. 5 and 30)as needed so that target MS location data can be generated that isuniform and consistent with location data generated from other targetMSs 140. In particular, such uniformity and consistency is both in termsof data structures and interpretation of signal characteristic valuesprovided by the MS location data, as will be described hereinbelow.Note, this step may also only be performed if the gateway provides suchmeasurements to a FOM. Otherwise, such FOM is likely to perform suchfiltering;(23.3) inputting the generated target MS location data to one or more MSlocation estimating models (FOMs, labeled collectively as 1224 in FIG.5), so that each such FOM may use the input target MS location data forgenerating a “location hypothesis” providing an estimate of the locationof the target MS 140. Note, this step may also only be performed if thegateway provides such measurements to a FOM;(23.4) receiving the resulting location hypotheses from the activatedFOMs, and providing the generated location hypotheses to an hypothesisevaluation module (denoted the hypothesis evaluator 1228 in FIG. 5) for:

(a) (optionally) adjusting the target MS location estimates of thegenerated location hypotheses and/or adjusting confidence values of thelocation hypotheses, wherein for each location hypothesis, itsconfidence value indicates the confidence or likelihood that the targetMS is located in the location estimate of the location hypothesis.Moreover, note that such adjusting uses archival information related tothe accuracy and/or reliability of previously generated locationhypotheses;

(b) (optionally) evaluating the location hypotheses according to variousheuristics related to, for example, the radio coverage area 120 terrain,the laws of physics, characteristics of likely movement of the target MS140; and

(c) (necessarily) determining a most likely location area for the targetMS 140, wherein the measurement of confidence associated with each inputMS location area estimate may be used for determining a “most likelylocation area”; and

(23.5) outputting a most likely target MS location estimate to one ormore applications 146 (FIG. 5) requesting an estimate of the location ofthe target MS 140.

Location Hypothesis Data Representation

In order to describe how the steps (23.1) through (23.5) are performedin the sections below, some introductory remarks related to the datadenoted above as location hypotheses will be helpful. Additionally, itwill also be helpful to provide introductory remarks related tohistorical location data and the data base management programsassociated therewith.

For each target MS location estimate generated and utilized by thewireless location capabilities disclosed herein, the location estimateis provided in a data structure (or object class) denoted as a “locationhypothesis” (illustrated in Table LH-1). Brief descriptions of the datafields for a location hypothesis is provided in the Table LH-1.

TABLE LH-1 FOM_ID First order model ID (providing this LocationHypothesis); note, since it is possible for location hypotheses to begenerated by other than the FOMs 1224, in general, this field identifiesthe module that generated this location hypothesis. MS_ID Theidentification of the target MS 140 to this location hypothesis applies.pt_est The most likely location point estimate of the target MS 140.valid_pt Boolean indicating the validity of “pt_est”. area_est LocationArea Estimate of the target MS 140 provided by the FOM. This areaestimate will be used whenever “image_area” below is NULL. valid_areaBoolean indicating the validity of “area_est” (one of “pt_est“ and“area_est” must be valid). adjust Boolean (true if adjustments to thefields of this location hypothesis are to be performed in the Contextadjuster Module). pt_covering Reference to a substantially minimal area(e.g., mesh cell) covering of “pt_est”. Note, since this MS 140 maybesubstantially on a cell boundary, this covering may, in some cases,include more than one cell. image_area Reference to a substantiallyminimal area (e.g., mesh cell) covering of “pt_covering” (see detaileddescription of the function, “confidence_adjuster”). Note that if thisfield is not NULL, then this is the target MS location estimate used bythe location center 142 instead of “area_est”. extrapolation_areaReference to (if non-NULL) an extrapolated MS target estimate areaprovided by the location extrapolator submodule 1432 of the hypothesisanalyzer 1332. That is, this field, if non-NULL, is an extrapolation ofthe “image_area” field if it exists, otherwise this field is anextrapolation of the “area_est” field. Note other extrapolation fieldsmay also be provided depending on the embodiment of the wirelesslocation capabilities disclosed herein, such as an extrapolation of the“pt_covering”. confidence In one embodiment, this is a probabilityindicating a likelihood that the target MS 140 is in (or out) of aparticular area. If “image_area” exists, then this is a measure of thelikelihood that the target MS 140 is within the area represented by“image_area“, or if “image_area” has not been computed (e.g., “adjust”is FALSE), then “area_est” must be valid and this is a measure of thelikelihood that the target MS 140 is within the area represented by“area_est”. Other embodiments, are also within the scope of the wirelesslocation capabilities disclosed herein that are not probabilities; e.g.,translations and/or expansions of the range as one skilled in the artwill understand. Original_Timestamp Date and time that the locationsignature cluster (defined hereinbelow) for this location hypothesis wasreceived by the signal processing subsystem 1220. Active_TimestampRun-time field providing the time to which this location hypothesis hashad its MS location estimate(s) extrapolated (in the locationextrapolator 1432 of the hypothesis analyzer 1332). Note that this fieldis initialized with the value from the “Original_Timestamp” field.Processing Tags For indicating particular types of environmental andenvironmental classifications not readily determined by thecategorizations “Original_Timestamp” field (e.g., weather, traffic), andrestrictions on location hypothesis processing. loc_sig_cluster Providesaccess to the collection of location signature signal characteristicsderived from communications between the target MS 140 and the basestation(s) detected by this MS (discussed in detail hereinbelow); inparticular, the location data accessed here is provided to the firstorder models by the signal processing subsystem 1220; i.e., access tothe “loc sigs” (received at “timestamp” regarding the location of thetarget MS) descriptor Original descriptor (from the First order modelindicating why/how the Location Area Estimate and Confidence Value weredetermined).

As can be seen in the Table LH-1, each location hypothesis datastructure includes at least one measurement, denoted hereinafter as aconfidence value (or simply confidence), that is a measurement of theperceived likelihood that an MS location estimate in the locationhypothesis is an accurate location estimate of the target MS 140. Since,in some embodiments of the wireless location capabilities disclosedherein, such confidence values are an important aspect, much of thedescription and use of such confidence values are described below;however, a brief description is provided here.

In one embodiment, each confidence value is a probability indicative ofa likeliness that the target MS 140 resides within an geographic arearepresented by the hypothesis to which the confidence value applies.Accordingly, each such confidence value is in the range [0, 1].Moreover, for clarity of discussion, it is assumed that unless statedotherwise that the probabilistic definition provided here is to be usedwhen confidence values are discussed.

Note, however, other definitions of confidence values are within thescope of the wireless location capabilities disclosed herein that may bemore general than probabilities, and/or that have different ranges otherthan [0, 1]. For example, one such alternative is that each suchconfidence value is in the range −1.0 to 1.0, wherein the larger thevalue, the greater the perceived likelihood that the target MS 140 is in(or at) a corresponding MS location estimate of the location hypothesisto which the confidence value applies. As an aside, note that a locationhypothesis may have more than one MS location estimate (as will bediscussed in detail below) and the confidence value will typically onlycorrespond or apply to one of the MS location estimates in the locationhypothesis. Further, values for the confidence value field may beinterpreted as: (a)−1.0 means that the target MS 140 is NOT in such acorresponding MS area estimate of the location hypothesis area, (b) 0means that it is unknown as to the likelihood of whether the MS 140 inthe corresponding MS area estimate, and (c)+1.0 means that the MS 140 isperceived to positively be in the corresponding MS area estimate.

Additionally, in utilizing location hypotheses in, for example, thelocation evaluator 1228 as in (23.4) above, it is important to keep inmind that for confidences, cf₁ and cf₂, if cf₁<=cf₂, then for a locationhypotheses H₁ and H₂ having cf₁ and cf₂, respectively, the target MS 140is expected to more likely reside in a target MS estimate of H₂ than atarget MS estimate of H₁. Moreover, if an area, A, is such that it isincluded in a plurality of location hypothesis target MS estimates, thena confidence score, CS_(A), can be assigned to A, wherein the confidencescore for such an area is a function of the confidences for all thelocation hypotheses whose (most pertinent) target MS location estimatescontain A. That is, in order to determine a most likely target MSlocation area estimate for outputting from the location center/gateway142, a confidence score is determined for areas within the locationcenter/gateway service area.

Coverage Area: Area Types and their Determination

The notion of “area type” as related to wireless signal transmissioncharacteristics has been used in many investigations of radio signaltransmission characteristics. Some investigators, when investigatingsuch signal characteristics of areas have used somewhat naive areaclassifications such as urban, suburban, rural, etc. However, it isdesirable for the purposes of the wireless location capabilitiesdisclosed herein to have a more operational definition of area typesthat is more closely associated with wireless signal transmissionbehaviors.

To describe embodiments of the an area type scheme that may be used inthe wireless location capabilities disclosed herein, some introductoryremarks are first provided. Note that the wireless signal transmissionbehavior for an area depends on at least the following criteria:

-   -   (23.8.1) substantially invariant terrain characteristics (both        natural and man-made) of the area; e.g., mountains, buildings,        lakes, highways, bridges, building density;    -   (23.8.2) time varying environmental characteristics (both        natural and man-made) of the area; e.g., foliage, traffic,        weather, special events such as baseball games;    -   (23.8.3) wireless communication components or infrastructure in        the area; e.g., the arrangement and signal communication        characteristics of the base stations 122 in the area (e.g., base        station antenna downtilt). Further, the antenna characteristics        at the base stations 122 may be important criteria.

Accordingly, a description of wireless signal characteristics fordetermining area types could potentially include a characterization ofwireless signaling attributes as they relate to each of the abovecriteria. Thus, an area type might be: hilly, treed, suburban, having nobuildings above 50 feet, with base stations spaced apart by two miles.However, a categorization of area types is desired that is both moreclosely tied to the wireless signaling characteristics of the area, andis capable of being computed substantially automatically and repeatedlyover time. Moreover, for a wireless location system, the primarywireless signaling characteristics for categorizing areas into at leastminimally similar area types are: thermal noise and, more importantly,multipath characteristics (e.g., multipath fade and time delay).

Focusing for the moment on the multipath characteristics, it is believedthat (23.8.1) and (23.8.3) immediately above are, in general, moreimportant criteria for accurately locating an MS 140 than (23.8.2). Thatis, regarding (23.8.1), multipath tends to increase as the density ofnearby vertical area changes increases. For example, multipath isparticularly problematic where there is a high density of high risebuildings and/or where there are closely spaced geographic undulations.In both cases, the amount of change in vertical area per unit of area ina horizontal plane (for some horizontal reference plane) may be high.Regarding (23.8.3), the greater the density of base stations 122, theless problematic multipath may become in locating an MS 140. Moreover,the arrangement of the base stations 122 in the radio coverage area 120in FIG. 4 may affect the amount and severity of multipath.

Accordingly, it would be desirable to have a method and system forstraightforwardly determining area type classifications related tomultipath, and in particular, multipath due to (23.8.1) and (23.8.3).The wireless location capabilities disclosed herein provides such adetermination by utilizing a novel notion of area type, hereinafterdenoted “transmission area type” (or, “area type” when both a genericarea type classification scheme and the transmission area type discussedhereinafter are intended) for classifying “similar” areas, wherein eachtransmission area type class or category is intended to describe an areahaving at least minimally similar wireless signal transmissioncharacteristics. That is, the novel transmission area type scheme of thewireless location capabilities disclosed herein is based on: (a) theterrain area classifications; e.g., the terrain of an area surrounding atarget MS 140, (b) the configuration of base stations 122 in the radiocoverage area 120, and (c) characterizations of the wireless signaltransmission paths between a target MS 140 location and the basestations 122.

In one embodiment of a method and system for determining such(transmission) area type approximations, a partition (denotedhereinafter as P₀) is imposed upon the radio coverage area 120 forpartitioning for radio coverage area into subareas, wherein each subareais an estimate of an area having included MS 140 locations that arelikely to have is at least a minimal amount of similarity in theirwireless signaling characteristics. To obtain the partition P₀ of theradio coverage area 120, the following steps are performed:

-   -   (23.8.4.1) Partition the radio coverage area 120 into subareas,        wherein in each subarea is: (a) connected, (b) the subarea is        not too oblong, e.g., the variations in the lengths of chords        sectioning the subarea through the centroid of the subarea are        below a predetermined threshold, (c) the size of the subarea is        below a predetermined value, and (d) for most locations (e.g.,        within a first or second deviation) within the subarea whose        wireless signaling characteristics have been verified, it is        likely (e.g., within a first or second deviation) that an MS 140        at one of these locations will detect (forward transmission        path) and/or will be detected (reverse transmission path) by a        same collection of base stations 122. For example, in a CDMA        context, a first such collection may be (for the forward        transmission path) the active set of base stations 122, or, the        union of the active and candidate sets, or, the union of the        active, candidate and/or remaining sets of base stations 122        detected by “most” MSs 140 in. Additionally (or alternatively),        a second such collection may be the base stations 122 that are        expected to detect MSs 140 at locations within the subarea. Of        course, the union or intersection of the first and second        collections is also within the scope of the wireless location        capabilities disclosed herein for partitioning the radio        coverage area 120 according to (d) above. It is worth noting        that it is believed that base station 122 power levels will be        substantially constant. However, even if this is not the case,        one or more collections for (d) above may be determined        empirically and/or by computationally simulating the power        output of each base station 122 at a predetermined level.        Moreover, it is also worth mentioning that this step is        relatively straightforward to implement using the data stored in        the location signature data base 1320 (i.e., the verified        location signature clusters discussed in detail hereinbelow).        Denote the resulting partition here as P₁.    -   (23.8.4.2) Partition the radio coverage area 120 into subareas,        wherein each subarea appears to have substantially homogeneous        terrain characteristics. Note, this may be performed        periodically substantially automatically by scanning radio        coverage area images obtained from aerial or satellite imaging.        For example, EarthWatch Inc. of Longmont, Colo. can provide        geographic with 3 meter resolution from satellite imaging data.        Denote the resulting partition here as P₂.    -   (23.8.4.3) Overlay both of the above partitions, P₁ and P₂ of        the radio coverage area 120 to obtain new subareas that are        intersections of the subareas from each of the above partitions.        This new partition is P₀ (i.e., P₀=P₁ intersect P₂), and the        subareas of it are denoted as “P₀ subareas”.

Now assuming P₀ has been obtained, the subareas of P₀ are provided witha first classification or categorization as follows:

-   -   (23.8.4.4) Determine an area type categorization scheme for the        subareas of P₁. For example, a subarea, A, of P₁, may be        categorized or labeled according to the number of base stations        122 in each of the collections used in (23.8.4.1)(d) above for        determining subareas of P₁. Thus, in one such categorization        scheme, each category may correspond to a single number x (such        as 3), wherein for a subarea, A, of this category, there is a        group of x (e.g., three) base stations 122 that are expected to        be detected by a most target MSs 140 in the area A. Other        embodiments are also possible, such as a categorization scheme        wherein each category may correspond to a triple: of numbers        such as (5, 2, 1), wherein for a subarea A of this category,        there is a common group of 5 base stations 122 with two-way        signal detection expected with most locations (e.g., within a        first or second deviation) within A, there are 2 base stations        that are expected to be detected by a target MS 140 in A but        these base stations can not detect the target MS, and there is        one base station 122 that is expected to be able to detect a        target MS in A but not be detected.    -   (23.8.4.5) Determine an area type categorization scheme for the        subareas of P₂. Note that the subareas of P₂ may be categorized        according to their similarities. In one embodiment, such        categories may be somewhat similar to the naive area types        mentioned above (e.g., dense urban, urban, suburban, rural,        mountain, etc.). However, it is also an aspect of the wireless        location capabilities disclosed herein that more precise        categorizations may be used, such as a category for all areas        having between 20,000 and 30,000 square feet of vertical area        change per 11,000 square feet of horizontal area and also having        a high traffic volume (such a category likely corresponding to a        “moderately dense urban” area type).    -   (23.8.4.6) Categorize subareas of P₀ with a categorization        scheme denoted the “P₀ categorization,” wherein for each P₀        subarea, A, a “P₀ area type” is determined for A according to        the following substep(s):        -   (a) Categorize A by the two categories from (23.8.4.4) and            (23.8.5) with which it is identified. Thus, A is categorized            (in a corresponding P₀ area type) both according to its            terrain and the base station infrastructure configuration in            the radio coverage area 120.    -   (23.8.4.7) For each P₀ subarea, A, of P₀ perform the following        step(s):        -   (a) Determine a centroid, C(A), for A;        -   (b) Determine an approximation to a wireless transmission            path between C(A) and each base station 122 of a            predetermined group of base stations expected to be in (one            and/or two-way) signal communication with most target MS 140            locations in A. For example, one such approximation is a            straight line between C(A) and each of the base stations 122            in the group. However, other such approximations are within            the scope of the wireless location capabilities disclosed            herein, such as, a generally triangular shaped area as the            transmission path, wherein a first vertex of this area is at            the corresponding base station for the transmission path,            and the sides of the generally triangular shaped defining            the first vertex have a smallest angle between them that            allows A to be completely between these sides.        -   (c) For each base station 122, BS_(i), in the group            mentioned in (b) above, create an empty list, BS_(i)-list,            and put on this list at least the P₀ area types for the            “significant” P₀ subareas crossed by the transmission path            between C(A) and BS_(i). Note that “significant” P₀ subareas            may be defined as, for example, the P₀ subareas through            which at least a minimal length of the transmission path            traverses. Alternatively, such “significant” P₀ subareas may            be defined as those P₀ subareas that additionally are know            or expected to generate substantial multipath.        -   (d) Assign as the transmission area type for A as the            collection of BS_(i)-lists. Thus, any other P₀ subarea            having the same (or substantially similar) collection of            lists of P₀ area types will be viewed as having            approximately the same radio transmission characteristics.

Note that other transmission signal characteristics may be incorporatedinto the transmission area types. For example, thermal noisecharacteristics may be included by providing a third radio coverage area120 partition, P₃, in addition to the partitions of P₁ and P₂ generatedin (23.8.4.1) and (23.8.4.2) respectively. Moreover, the time varyingcharacteristics of (23.8.2) may be incorporated in the transmission areatype frame work by generating multiple versions of the transmission areatypes such that the transmission area type for a given subarea of P₀ maychange depending on the combination of time varying environmentalcharacteristics to be considered in the transmission area types. Forinstance, to account for seasonality, four versions of the partitions P₁and P₂ may be generated, one for each of the seasons, and subsequentlygenerate a (potentially) different partition P₀ for each season.Further, the type and/or characteristics of base station 122 antennasmay also be included in an embodiment of the transmission area type.

Other embodiments of area types are also within the scope of thewireless location capabilities disclosed herein. As mentioned above,each of the first order models 1224 have default confidence valuesassociated therewith, and these confidence values may be probabilities.More precisely, such probability confidence values can be determined asfollows. Assume there is a partition of the coverage area into subareas,each subarea being denoted a “partition area.” For each partition area,activate each first order model 1224 with historical location data inthe Location Signature Data Base 1320 (FIG. 6), wherein the historicallocation data has been obtained from corresponding known mobile stationlocations in the partition area. For each first order model, determine aprobability of the first order model generating a location hypothesiswhose location estimate contains the corresponding known mobile stationlocation. To accomplish this, assume the coverage area is partitionedinto partition areas A, wherein each partition area A is specified asthe collection of coverage area locations such that for each location,the detected wireless transmissions between the network base stationsand a target mobile station at the location can be straightforwardlyequated with other locations of area A. For example, one such partition,P₀, can be defined wherein each partition area A is specified in termsof three sets of base station identifiers, namely, (a) the base stationidentifiers of the base stations that can be both detected at eachlocation of A and can detect a target mobile station at each location,(b) the identifiers for base stations that can detect a target mobilestation at each location of A, but can not be detected by the targetmobile station, and (c) the identifiers for base stations that can bedetected by a target mobile station at each location of A, but thesebase stations can not detect the target mobile station. That is, twolocations, I₁ and I₂. are identified as being in A if and only if thethree sets of (a), (b), and (c) for 1, are, respectively, identical tothe three sets of (a), (b), and (c) for I₂.

Accordingly, assuming the partition P₀ is used, a description can begiven as to how probabilities may be assigned as the confidence valuesof location hypotheses generated by the first order models 1224. Foreach partition area A, a first order model 1224 is supplied withwireless measurements of archived location data in the LocationSignature Data Base associated with corresponding verified mobilestation locations. Thus, a probability can be determined as to howlikely the first order model is to generate a location hypothesis havinga location estimate containing the corresponding verified mobile stationlocation. Accordingly, a table of partition area probabilities can bedetermined for each first order model 1224. Thus, when a locationhypothesis is generated and identified as belonging to one of thepartition areas, the corresponding probability for that partition areamay be assigned as the confidence value for the location hypothesis. Theadvantages to using actual probabilities here is that, as will bediscussed below, the most likelihood estimator 1344 can compute astraightforward probability for each distinct intersection of themultiple location hypotheses generated by the multiple first ordermodels, such that each such probability indicates a likelihood that thetarget mobile station is in the corresponding intersection.

Location Information Data Bases and Data Location Data BasesIntroduction

It is an aspect of the wireless location capabilities disclosed hereinthat MS location processing performed by the location center/gateway 142should become increasingly better at locating a target MS 140 both by(a) building an increasingly more detailed model of the signalcharacteristics of locations in the service area for the wirelesslocation capabilities disclosed herein, and also (b) by providingcapabilities for the location center processing to adapt toenvironmental changes.

One way these aspects of the wireless location capabilities disclosedherein are realized is by providing one or more data base managementsystems and data bases for:

(a) storing and associating wireless MS signal characteristics withknown locations of MSs 140 used in providing the signal characteristics.Such stored associations may not only provide an increasingly bettermodel of the signal characteristics of the geography of the servicearea, but also provide an increasingly better model of more changeablesignal characteristic affecting environmental factors such as weather,seasons, and/or traffic patterns;

(b) adaptively updating the signal characteristic data stored so that itreflects changes in the environment of the service area such as, forexample, a new high rise building or a new highway.

Referring again to FIG. 5 of the collective representation of these databases is the location information data bases 1232. Included among thesedata bases is a data base for providing training and/or calibration datato one or more trainable/calibratable FOMs 1224, as well as an archivaldata base for archiving historical MS location information related tothe performance of the FOMs. These data bases will be discussed asnecessary hereinbelow. However, a further brief introduction to thearchival data base is provided here. Accordingly, the term, “locationsignature data base” is used hereinafter to denote the archival database and/or data base management system depending on the context of thediscussion. The location signature data base (shown in, for example,FIG. 6 and labeled 1320) is a repository for wireless signalcharacteristic data derived from wireless signal communications betweenan MS 140 and one or more base stations 122, wherein the correspondinglocation of the MS 140 is known and also stored in the locationsignature data base 1320. More particularly, the location signature database 1320 associates each such known MS location with the wirelesssignal characteristic data derived from wireless signal communicationsbetween the MS 140 and one or more base stations 122 at this MSlocation. Accordingly, it is an aspect of the wireless locationcapabilities disclosed herein to utilize such historical MS signallocation data for enhancing the correctness and/or confidence of certainlocation hypotheses as will be described in detail in other sectionsbelow.

Data Representations for the Location Signature Data Base

In one embodiment, there are four fundamental entity types (or objectclasses in an object oriented programming paradigm) utilized in thelocation signature data base 1320. Briefly, these data entities aredescribed in the items (24.1) through (24.4) that follow:

(24.1) (verified) location signatures: Each such (verified) locationsignature describes the wireless signal characteristic measurementsbetween a given base station (e.g., BS 122 or LBS 152) and an MS 140 ata (verified or known) location associated with the (verified) locationsignature. That is, a verified location signature corresponds to alocation whose coordinates such as latitude-longitude coordinates areknown, while simply a location signature may have a known or unknownlocation corresponding with it. Note that the term (verified) locationsignature is also denoted by the abbreviation, “(verified) loc sig”hereinbelow;(24.2) (verified) location signature clusters: Each such (verified)location signature cluster includes a collection of (verified) locationsignatures corresponding to all the location signatures between a targetMS 140 at a (possibly verified) presumed substantially stationarylocation and each BS (e.g., 122 or 152) from which the target MS 140 candetect the BS's pilot channel regardless of the classification of the BSin the target MS (i.e., for CDMA, regardless of whether a BS is in theMS's active, candidate or remaining base station sets, as one skilled inthe art will understand). Note that for simplicity here, it is presumedthat each location signature cluster has a single fixed primary basestation to which the target MS 140 synchronizes or obtains its timing;(24.3) “composite location objects (or entities)”: Each such entity is amore general entity than the verified location signature cluster. Anobject of this type is a collection of (verified) location signaturesthat are associated with the same MS 140 at substantially the samelocation at the same time and each such loc sig is associated with adifferent base station. However, there is no requirement that a loc sigfrom each BS 122 for which the MS 140 can detect the BS's pilot channelis included in the “composite location object (or entity)”; and(24.4) MS location estimation data that includes MS location estimatesoutput by one or more MS location estimating first order models 1224,such MS location estimate data is described in detail hereinbelow.

It is important to note that a loc sig is, in one embodiment, aninstance of the data structure containing the signal characteristicmeasurements output by the signal filtering and normalizing subsystemalso denoted as the signal processing subsystem 1220 describing thesignals between: (i) a specific base station 122 (BS) and (ii) a mobilestation 140 (MS), wherein the BS's location is known and the MS'slocation is assumed to be substantially constant (during a 2-5 secondinterval in one embodiment of the wireless location capabilitiesdisclosed herein), during communication with the MS 140 for obtaining asingle instance of loc sig data, although the MS location may or may notbe known. Further, for notational purposes, the BS 122 and the MS 140for a loc sig hereinafter will be denoted the “BS associated with theloc sig”, and the “MS associated with the loc sig” respectively.Moreover, the location of the MS 140 at the time the loc sig data isobtained will be denoted the “location associated with the loc sig”(this location possibly being unknown).

Note that additional description of this aspect of the wireless locationcapabilities disclosed herein can be found in one of the following twocopending U.S. patent applications which are incorporated herein byreference: (a) “Location Of A Mobile Station” filed Nov. 24, 1999 havingapplication Ser. No. 09/194,367 whose inventors are D. J. Dupray and C.L. Karr, and (b) “A Wireless Location System For Calibrating MultipleLocation Estimators” filed Oct. 21, 1998 having application Ser. No.09/176,587 whose inventor is D. J. Dupray, wherein these copendingpatent applications may have essential material for the presentspecification. In particular, these copending patent applications mayhave essential material relating to the location signature data base1320.

Location Center Architecture Overview of Location Center/GatewayFunctional Components

FIG. 5 presents a high level diagram of an embodiment of the locationcenter/gateway 142 and the location engine 139 in the context of theinfrastructure for the entire location system of the wireless locationcapabilities disclosed herein.

It is important to note that the architecture for the locationcenter/gateway 142 and the location engine 139 provided by the wirelesslocation capabilities disclosed herein is designed for extensibility andflexibility so that MS 140 location accuracy and reliability may beenhanced as further location data become available and as enhanced MSlocation techniques become available. In addressing the design goals ofextensibility and flexibility, the high level architecture forgenerating and processing MS location estimates may be considered asdivided into the following high level functional groups describedhereinbelow.

Low Level Wireless Signal Processing Subsystem for Receiving andConditioning Wireless Signal Measurements

A first functional group of location engine 139 modules is forperforming signal processing and filtering of MS location signal datareceived from a conventional wireless (e.g., CDMA) infrastructure, asdiscussed in the steps (23.1) and (23.2) above. This group is denotedthe signal processing subsystem 1220 herein. One embodiment of such asubsystem is described in the U.S. copending patent application titled,“Wireless Location Using A Plurality of Commercial NetworkInfrastructures,” by F. W. LeBlanc, Dupray and Karr filed Jan. 22, 1999and having U.S. Pat. No. 6,236,365. Note that this copending patentapplication is incorporated herein entirely by reference since it maycontain essential material for the wireless location capabilitiesdisclosed herein. In particular, regarding the signal processingsubsystem 20. Note, however, that the signal processing subsystem may beunnecessary for the gateway 142 unless the gateway supplies wirelesslocation signal data to one or more FOMs.

Initial Location Estimators: First Order Models

A second functional group of modules at least accessible by the locationengine 139 are the FOM 1224 for generating various target MS 140location initial estimates, as described in step (23.3). A briefdescription of some types of first order models is provided immediatelybelow. Note that FIG. 8 illustrates another, more detail view of anembodiment of the location center/gateway 142 for the wireless locationcapabilities disclosed herein. In particular, this figure illustratessome of the FOMs 1224 at least accessible (but not necessarilyco-located with the other location center/gateway modules shown in thisfigure), and additionally illustrates the primary communications withother modules of the gateway. However, it is important to note that thewireless location capabilities disclosed herein is not limited to theFOMs 1224 shown and discussed herein. That is, it is a primary aspect ofthe wireless location capabilities disclosed herein to easilyincorporate FOMs using other signal processing and/or computationallocation estimating techniques than those presented herein. Further,note that each FOM type may have a plurality of its MS locationestimating models (at least) accessible by the gateway 142.

For example, (as will be described in further detail below), one suchtype of model or FOM 1224 (hereinafter models of this type are referredto as “terrestrial communication station offset (TCSO) models” or“terrestrial communication station offset (TCSO) first order models”, or“terrestrial communication station offset (TCSO) FOMs”) may be based ona range, offset, and/or distance computation such as on a base stationsignal reception angle determination between the target MS 140 from eachof one or more base stations. Basically, such TCSO models 1224 determinea location estimate of the target MS 140 by determining an offset fromeach of one or more base stations 122, possibly in a particulardirection from each (some of) the base stations, so that, e.g., anintersection of each area locus defined by the base station offsets mayprovide an estimate of the location of the target MS. TCSO FOMs 1224 maycompute such offsets based on, e.g.:

-   -   (a) signal timing measurements between the target mobile station        140 and one or more base stations 122; e.g., timing measurements        such as time difference of arrival (TDOA), or time of arrival        (TOA). Note that both forward and reverse signal path timing        measurements may be utilized;    -   (b) signal strength measurements (e.g., relative to power        control settings of the MS 140 and/or one or more BS 122);        and/or    -   (c) signal angle of arrival measurements, or ranges thereof, at        one or more base stations 122 (such angles and/or angular ranges        provided by, e.g., base station antenna sectors having angular        ranges of 120° or 60°, or, so called “SMART antennas” with        variable angular transmission ranges of 2° to 120°).        Accordingly, a terrestrial communication station offset (TCSO)        model may utilize, e.g., triangulation or trilateration to        compute a location hypothesis having either an area location or        a point location for an estimate of the target MS 140.        Additionally, in some embodiments location hypothesis may        include an estimated error.

Another type of FOM 1224 is a statistically based first order model1224, wherein a statistical technique, such as regression techniques(e.g., least squares, partial least squares, principle decomposition),or e.g., Bollenger Bands (e.g., for computing minimum and maximum basestation offsets). In general, models of this type output locationhypotheses determined by performing one or more statistical techniquesor comparisons between the verified location signatures in locationsignature data base 1320, and the wireless signal measurements from atarget MS. Models of this type are also referred to hereinafter as a“stochastic signal (first order) model” or a “stochastic FOM” or a“statistical model.” Of course, statistically based FOMs may be a hybridcombination with another type of FOM such as a TCSO FOM.

Still another type of FOM 1224 is an adaptive learning model, such as anartificial neural net or a genetic algorithm, wherein the FOM may betrained to recognize or associate each of a plurality of locations witha corresponding set of signal characteristics for communications betweenthe target MS 140 (at the location) and the base stations 122. Moreover,typically such a FOM is expected to accurately interpolate/extrapolatetarget MS 140 location estimates from a set of signal characteristicsfrom an unknown target MS 140 location. Models of this type are alsoreferred to hereinafter variously as “artificial neural net models” or“neural net models” or “trainable models” or “learning models.” Notethat a related type of FOM 1224 is based on pattern recognition. TheseFOMs can recognize patterns in the signal characteristics ofcommunications between the target MS 140 (at the location) and the basestations 122 and thereby estimate a location area of the target MS.However, such FOMs may not be trainable.

Yet another type of FOM 1224 can be based on a collection of dispersedlow power, low cost fixed location wireless transceivers (also denoted“location base stations 152” hereinabove) that are provided fordetecting a target MS 140 in areas where, e.g., there is insufficientbase station 122 infrastructure coverage for providing a desired levelof MS 140 location accuracy. For example, it may uneconomical to providehigh traffic wireless voice coverage of a typical wireless base station122 in a nature preserve or at a fair ground that is only populated afew days out of the year. However, if such low cost location basestations 152 can be directed to activate and deactivate via thedirection of a FOM 1224 of the present type, then these location basestations can be used to both location a target MS 140 and also provideindications of where the target MS is not. For example, if there arelocation base stations 152 populating an area where the target MS 140 ispresumed to be, then by activating these location base stations 152,evidence may be obtained as to whether or not the target MS is actuallyin the area; e.g., if the target MS 140 is detected by a location basestation 152, then a corresponding location hypothesis having a locationestimate corresponding to the coverage area of the location base stationmay have a very high confidence value. Alternatively, if the target MS140 is not detected by a location base station 152, then a correspondinglocation hypothesis having a location estimate corresponding to thecoverage area of the location base station may have a very lowconfidence value. Models of this type are referred to hereinafter as“location base station models.”

Yet another type of FOM 1224 can be based on input from a mobile basestation 148, wherein location hypotheses may be generated from target MS140 location data received from the mobile base station 148.

Still other types of FOM 1224 can be based on various techniques forrecognizing wireless signal measurement patterns and associatingparticular patterns with locations in the coverage area 120. Forexample, artificial neural networks or other learning models can used asthe basis for various FOMs.

Note that the FOM types mentioned here as well as other FOM types arediscussed in detail hereinbelow. Moreover, it is important to keep inmind that in one embodiment of the wireless location capabilitiesdisclosed herein, the substantially simultaneous use or activation of apotentially large number of such first order models 1224, may be able toenhance both the reliability of location estimates and the accuracy ofsuch estimates. Additionally, note that in some embodiments of thewireless location capabilities disclosed herein, the first order models1224 can be activated when appropriate signal measurements are obtained.For example, a TDOA FOM may be activated when only a single signal timedelay measurement is obtained from some plurality of base station 122.However, if, for instance, additional time delay values are obtained(and assuming such additional values are necessary), then one or morewireless signal pattern matching FOM may also be activated inconjunction with the TDOA FOM. Additionally, a FOM using satellitesignals (e.g., GPS) to perform a triangulation may be activated wheneverappropriate measurements are received regardless of whether additionalFOMs are capable of being substantially simultaneously activated or not.Accordingly, since such satellite signal FOMs are generally moreaccurate, output from such a FOM may dominate any other previous orsimultaneous estimates unless there is evidence to the contrary.

Moreover, the wireless location capabilities disclosed herein provides aframework for incorporating MS location estimators to be subsequentlyprovided as new FOMs in a straightforward manner. For example, a FOM1224 based on wireless signal time delay measurements from a distributedantenna system for wireless communication may be incorporated into thewireless location capabilities disclosed herein for thereby locating atarget MS 140 in an enclosed area serviced by the distributed antennasystem. Accordingly, by using such a distributed antenna FOM, thewireless location capabilities disclosed herein may determine the floorof a multi-story building from which a target MS is transmitting. Thus,MSs 140 can be located in three dimensions using such a distributedantenna FOM. Additionally, FOMs for detecting certain registrationchanges within, for example, a public switched telephone network canalso be used for locating a target MS 140. For example, for some MSs 140there may be an associated or dedicated device for each such MS thatallows the MS to function as a cordless phone to a line based telephonenetwork when the device detects that the MS is within signaling range.In one use of such a device (also denoted herein as a “home basestation”), the device registers with a home location register of thepublic switched telephone network when there is a status change such asfrom not detecting the corresponding MS to detecting the MS, or visaversa, as one skilled in the art will understand. Accordingly, byproviding a FOM that accesses the MS status in the home locationregister, the location engine 139 can determine whether the MS is withinsignaling range of the home base station or not, and generate locationhypotheses accordingly. Moreover, other FOMs based on, for example,chaos theory and/or fractal theory are also within the scope of thewireless location capabilities disclosed herein.

It is important to note the following aspects of the wireless locationcapabilities disclosed herein relating to FOMs 1224:

-   (28.1) Each such first order model 1224 may be relatively easily    incorporated into and/or removed from the wireless location    capabilities disclosed herein. For example, assuming that the signal    processing subsystem 1220 provides uniform input to the FOMs, and    there is a uniform FOM output interface (e.g., API), it is believed    that a large majority (if not substantially all) viable MS location    estimation strategies may be accommodated. Thus, it is    straightforward to add or delete such FOMs 1224.-   (28.2) First order models 1224 may be relatively simple and still    provide significant MS 140 locating functionality and    predictability. For example, much of what is believed to be common    or generic MS location processing has been coalesced into, for    example: a location hypothesis evaluation subsystem, denoted the    hypotheses evaluator 1228 and described immediately below. Thus, the    wireless location capabilities disclosed herein is modular and    extensible such that, for example, (and importantly) different first    order models 1224 may be utilized depending on the signal    transmission characteristics of the geographic region serviced by an    embodiment of the wireless location capabilities disclosed herein.    Thus, a simple configuration of the wireless location capabilities    disclosed herein may have (or access) a small number of FOMs 1224    for a simple wireless signal environment (e.g., flat terrain, no    urban canyons and low population density). Alternatively, for    complex wireless signal environments such as in cities like San    Francisco, Tokyo or New York, a large number of FOMs 1224 may be    simultaneously utilized for generating MS location hypotheses.

An Introduction to an Evaluator for Location Hypotheses: HypothesisEvaluator

A third functional group of location engine 139 modules evaluateslocation hypotheses output by the first order models 1224 and therebyprovides a “most likely” target MS location estimate. The modules forthis functional group are collectively denoted the hypothesis evaluator1228.

Hypothesis Evaluator

A primary purpose of the hypothesis evaluator 1228 is to mitigateconflicts and ambiguities related to location hypotheses output by thefirst order models 1224 and thereby output a “most likely” estimate ofan MS for which there is a request for it to be located. In providingthis capability, there are various related embodiments of the hypothesisevaluator that are within the scope of the wireless locationcapabilities disclosed herein. Since each location hypothesis includesboth an MS location area estimate and a corresponding confidence valueindicating a perceived confidence or likelihood of the target MS beingwithin the corresponding location area estimate, there is a monotonicrelationship between MS location area estimates and confidence values.That is, by increasing an MS location area estimate, the correspondingconfidence value may also be increased (in an extreme case, the locationarea estimate could be the entire coverage area 120 and thus theconfidence value may likely correspond to the highest level ofcertainty; i.e., +1.0). Accordingly, given a target MS location areaestimate (of a location hypothesis), an adjustment to its accuracy maybe performed by adjusting the MS location area estimate and/or thecorresponding confidence value. Thus, if the confidence value is, forexample, excessively low then the area estimate may be increased as atechnique for increasing the confidence value. Alternatively, if theestimated area is excessively large, and there is flexibility in thecorresponding confidence value, then the estimated area may be decreasedand the confidence value also decreased. Thus, if at some point in theprocessing of a location hypothesis, if the location hypothesis isjudged to be more (less) accurate than initially determined, then (i)the confidence value of the location hypothesis may be increased(decreased), and/or (ii) the MS location area estimate can be decreased(increased). Moreover, note that when the confidence values areprobabilities, such adjustments are may require the reactivation of oneor more FOMs 1224 with requests to generate location hypotheses havinglocation estimates of different sizes. Alternatively, adjuster modules1436 and/or 1440 (FIG. 16 discussed hereinbelow) may be invoked forgenerating location hypotheses having area estimates of different sizes.Moreover, the confidence value on such an adjusted location hypothesis(actually a new location hypothesis corresponding to the originallygenerated hypothesis) may also be a probability in that combinations ofFOMs 1224 and adjuster modules 1436 and 1440 can also be calibrated forthereby yielding probabilities as confidence values to the resultinglocation hypotheses.

In a first class of embodiments (typically wherein the confidence valuesare not maintained as probabilities), the hypothesis evaluator 1228evaluates location hypotheses and adjusts or modifies only theirconfidence values for MS location area estimates and subsequently usesthese MS location estimates with the adjusted confidence values fordetermining a “most likely” MS location estimate for outputting.Alternatively, in a second class of embodiments for the hypothesisevaluator 1228 (also typically wherein the confidence values are notmaintained as probabilities), MS location area estimates can be adjustedwhile confidence values remain substantially fixed. However, in onepreferred embodiment of the present embodiment, both location hypothesisarea estimates and confidence values are modified.

The hypothesis evaluator 1228 may perform any or most of the followingtasks depending on the embodiment of the hypothesis evaluator. That is,

-   (30.1) it may enhance the accuracy of an initial location hypothesis    generated by an FOM by using the initial location hypothesis as,    essentially, a query or index into the location signature data base    1320 for obtaining one or more corresponding enhanced location    hypotheses, wherein the enhanced location hypotheses have both an    adjusted target MS location area estimates and an adjusted    confidences based on past performance of the FOM in the location    service surrounding the target MS location estimate of the initial    location hypothesis;    Additionally, for embodiments of the hypothesis evaluator 1228    wherein the confidence values for location hypotheses are not    maintained as probabilities, the following additional tasks (30.2)    through (30.7) may be performed:-   (30.2) the hypothesis evaluator 1228 may utilize environmental    information to improve and reconcile location hypotheses supplied by    the first order models 1224. A basic premise in this context is that    the accuracy of the individual first order models may be affected by    various environmental factors such as, for example, the season of    the year, the time of day, the weather conditions, the presence of    buildings, base station failures, etc.;-   (30.3) the hypothesis evaluator 1228 may determine how well the    associated signal characteristics used for locating a target MS    compare with particular verified loc sigs stored in the location    signature data base 1320 (see the location signature data base    section for further discussion regarding this aspect of the wireless    location capabilities disclosed herein). That is, for a given    location hypothesis, verified loc sigs (which were previously    obtained from one or more verified locations of one or more MS's)    are retrieved for an area corresponding to the location area    estimate of the location hypothesis, and the signal characteristics    of these verified loc sigs are compared with the signal    characteristics used to generate the location hypothesis for    determining their similarities and subsequently an adjustment to the    confidence of the location hypothesis (and/or the size of the    location area estimate);-   (30.4) the hypothesis evaluator 1228 may determine if (or how well)    such location hypotheses are consistent with well known physical    constraints such as the laws of physics. For example, if the    difference between a previous (most likely) location estimate of a    target MS and a location estimate by a current location hypothesis    requires the MS to:    -   (a1) move at an unreasonably high rate of speed (e.g., 200 mph),        or    -   (b1) move at an unreasonably high rate of speed for an area        (e.g., 80 mph in a corn patch), or    -   (c1) make unreasonably sharp velocity changes (e.g., from 60 mph        in one direction to 60 mph in the opposite direction in 4 sec),        then the confidence in the current Location Hypothesis is likely        to be reduced.

Alternatively, if for example, the difference between a previouslocation estimate of a target MS and a current location hypothesisindicates that the MS is:

-   -   (a2) moving at an appropriate velocity for the area being        traversed, or    -   (b2) moving along an established path (e.g., a freeway),

then the confidence in the current location hypothesis may be increased.

-   (30.5) the hypothesis evaluator 1228 may determine consistencies and    inconsistencies between location hypotheses obtained from different    first order models. For example, if two such location hypotheses,    for substantially the same timestamp, have estimated location areas    where the target MS is likely to be and these areas substantially    overlap, then the confidence in both such location hypotheses may be    increased. Additionally, note that a velocity of an MS may be    determined (via deltas of successive location hypotheses from one or    more first order models) even when there is low confidence in the    location estimates for the MS, since such deltas may, in some cases,    be more reliable than the actual target MS location estimates;-   (30.6) the hypothesis evaluator 1228 determines new (more accurate)    location hypotheses from other location hypotheses. For example,    this module may generate new hypotheses from currently active ones    by decomposing a location hypothesis having a target MS location    estimate intersecting two radically different wireless signaling    area types. Additionally, this module may generate location    hypotheses indicating areas of poor reception; and-   (30.7) the hypothesis evaluator 1228 determines and outputs a most    likely location hypothesis for a target MS.

Note that additional description of the hypothesis evaluator 1228 can befound in one of the following two copending U.S. patent applicationswhich are incorporated herein by reference: (a) “Location Of A MobileStation” filed Nov. 24, 1999 having application Ser. No. 09/194,367whose inventors are D. J. Dupray and C. L. Karr, and (b) “A WirelessLocation System For Calibrating Multiple Location Estimators” filed Oct.21, 1998 having application Ser. No. 09/176,587 whose inventor is D. J.Dupray, wherein these copending patent applications may have essentialmaterial for the present specification. In particular, these copendingpatent applications may have essential material relating to theirdescriptions of the hypothesis evaluator.

Context Adjuster Introduction.

The context adjuster (alternatively denoted “location adjuster modules)1326 module enhances both the comparability and predictability of thelocation hypotheses output by the first order models 1224. In oneembodiment (typically where confidence values of location hypotheses arenot maintained as probabilities), this module modifies locationhypotheses received from the FOMs 1224 so that the resulting locationhypotheses output by the context adjuster 1326 may be further processeduniformly and substantially without concern as to differences inaccuracy between the first order models from which location hypothesesoriginate. Further, embodiments of the context adjuster may determinethose factors that are perceived to impact the perceived accuracy (e.g.,confidence) of the location hypotheses. For instance, environmentalcharacteristics may be taken into account here, such as time of day,season, month, weather, geographical area categorizations (e.g., denseurban, urban, suburban, rural, mountain, etc.), area subcategorizations(e.g., heavily treed, hilly, high traffic area, etc.).

In FIG. 16, two such adjuster modules are shown, namely, an adjuster forenhancing reliability 1436 and an adjuster for enhancing accuracy 1440.Both of these adjusters perform their location hypothesis adjustments inthe manner described above. The difference between these two adjustermodules 1436 and 1440 is primarily the size of the localized area“nearby” the newly generated location estimate. In particular, since itis believed that the larger (smaller) the localized nearby area is, themore likely (less likely) the corresponding adjusted image is to containthe target mobile station location, the adjuster for enhancingreliability 1436 may determine its localized areas “nearby” a newlygenerated location estimate as, for example, having a 40% largerdiameter (alternatively, area) than the location area estimate generatedby a first order model 1224. Alternatively, the adjuster for enhancingaccuracy 1444 may determine its localized areas “nearby” a newlygenerated location estimate as, for example, having a 30% smallerdiameter (alternatively, area) than the location area estimate generatedby a first order model 1224. Thus, each newly generated locationhypothesis can potentially be used to derive at least two additionaladjusted location hypotheses with some of these adjusted locationhypotheses being more reliable and some being more accurate than thelocation hypotheses generated directly from the first order models 1224.

Note that additional description of context adjuster aspects of thewireless location capabilities disclosed herein can be found in thefollowing two copending U.S. patent applications which are incorporatedherein by reference: (a) “Location Of A Mobile Station” filed Nov. 24,1999 having application Ser. No. 09/194,367 whose inventors are D. J.Dupray and C. L. Karr, and (b) “A Wireless Location System ForCalibrating Multiple Location Estimators” filed Oct. 21, 1998 havingapplication Ser. No. 09/176,587 whose inventor is D. J. Dupray, whereinthese copending patent applications may have essential material for thepresent specification. In particular, these copending patentapplications may have essential material relating to the contextadjuster 1326.

MS Status Repository Introduction

The MS status repository 1338 is a run-time storage manager for storinglocation hypotheses from previous activations of the location engine 139(as well as for storing the output “most likely” target MS locationestimate(s)) so that a target MS 140 may be tracked using target MSlocation hypotheses from previous location engine 139 activations todetermine, for example, a movement of the target MS 140 betweenevaluations of the target MS location.

Location Hypothesis Analyzer Introduction.

The location hypothesis analyzer 1332, may adjust confidence values ofthe location hypotheses, according to:

-   -   (a) heuristics and/or statistical methods related to how well        the signal characteristics for the generated target MS location        hypothesis matches with previously obtained signal        characteristics for verified MS locations.    -   (b) heuristics related to how consistent the location hypothesis        is with physical laws, and/or highly probable reasonableness        conditions relating to the location of the target MS and its        movement characteristics. For example, such heuristics may        utilize knowledge of the geographical terrain in which the MS is        estimated to be, and/or, for instance, the MS velocity,        acceleration or extrapolation of an MS position, velocity, or        acceleration.    -   (c) generation of additional location hypotheses whose MS        locations are consistent with, for example, previous estimated        locations for the target MS.

Note that additional description of this aspect of the wireless locationcapabilities disclosed herein can be found in one of the followingcopending U.S. patent application which is incorporated herein byreference: “Location Of A Mobile Station” filed Nov. 24, 1999 havingapplication Ser. No. 09/194,367 whose inventors are D. J. Dupray and C.L. Karr.

Most Likelihood Estimator

The most likelihood estimator 1344 is a module for determining a “mostlikely” location estimate for a target MS being located by the locationengine 139. The most likelihood estimator 1344 receives a collection ofactive or relevant location hypotheses from the hypothesis analyzer 1332and uses these location hypotheses to determine one or more most likelyestimates for the target MS 140.

There are various embodiments of the most likelihood estimator 1344 thatmay be utilized with the wireless location capabilities disclosedherein. One such embodiment will now be described. At a high level, anarea of interest is first determined which contains the target MS 140whose location is desired. This can be straightforwardly determined byidentifying the base stations 122 that can be detected by the target MS140 and/or the base stations 140 that can detect the target MS.Subsequently, assuming that this area of interest has been previouslypartitioned into “cells” (e.g., small rectangular areas of, for example,50 to 200 feet per side) and that the resulting location hypotheses forestimating the location of the target MS 140 each have a likelihoodprobability associated therewith, then for each such locationhypothesis, a probability (more generally confidence value) is capableof being assigned to each cell intersecting and/or included in theassociated target MS location estimate. In particular, for each locationhypothesis, a portion of the probability value, P, for the associatedlocation estimate, A, can be assigned to each cell, C, intersecting theestimate. One simple way to perform this is to divide P by the number ofcells C, and increment, for each cell C, a corresponding probabilityindicative of the target MS 140 being in C with the result from thedivision. One skilled in the art will readily recognize numerous otherways of incrementing such cell probabilities, including: providing aGaussian or other probabilistic distribution of probability valuesaccording to, e.g., the distance of the cell from the centroid of thelocation estimate. Accordingly, assuming all such probability incrementshave been assigned to all such cells C from all location hypothesesgenerated for locating the target MS 140, then the following is oneembodiment of a program for determining one or more most likelylocations of the target MS.

Desired_rel ← get the desired reliability for the resulting locationestimate; Max_size ← get the desired maximum extent for the resultinglocation estimate; Binned_cells ← sort the cells of the area of interestby their probabilities into bins where each successive bin     includesthose cells whose confidence values are within a smaller(non-overlapping) range     from that of any preceding bin. Further,assume there are, e.g., 100 bins B_(I) wherein B₁ has     cells withconfidences within the range [0, 0.1], and B_(I) has cells withconfidences within the     range [(i − 1) * 0.01, i * 0.01]. Result ←nil; Curr_rel ← 0; /* current likelihood of target MS 140 being in thearea represented by “Result” */ Done ← FALSE; Repeat   Cell_bin ← getfirst (next) bin of cells from Binned_cells;   While (there are cells inCell_bin) do     Curr_cell ← get a next cell from Cell_bin that isclosest to the centroid of “Result”;     Result ← Result + Curr_cell;    /* now determine a new reliability value corresponding to adding“Curr_cell” to the most likely      location estimate being built in“Result” */     Curr_rel ← Curr_rel + confidence_of MS_in(Curr_cell);    If (Curr_rel > Desired_rel) then       Done ← TRUE; Until Done; /*reliability that the target MS is in “Result” is sufficient */ Curr_size← current maximum geographic extent (i.e., dimension) of the arearepresented by “Result”; If (Curr_size <= Max_size) then output(Result);Else Determine whether “Result” has one or more outlying cells that canbe replaced by other cells closer to the   centroid of “Result” andstill have a reliability >= “Desired_rel”;   If (there are replaceableoutlier cells) then    replace them in Result and output(Result);   Elseoutput(Result);

Note that numerous similar embodiments of the above program maybe used,as one skilled in the art will understand. For instance, instead of“building” Result as provided in the above program, Result can be“whittled” from the area of interest. Accordingly, Result would beinitialized to the entire area of interest, and cells would be selectedfor removal from Result. Additionally, note that the above programdetermines a fast approximation to the optimal most likely areacontaining the target MS 140 having at least a particular desiredconfidence. However, a similar program may be readily provided where amost likely area having less than a desired extent or dimension isoutput; e.g., such a program would could be used to provide an answer tothe question: “What city block is the target MS most likely in?”

Additionally, note that a center of gravity type of computation forobtaining the most likely location estimate of the target MS 140 may beused as described in U.S. Pat. No. 5,293,642 ('642 patent) filed Dec.19, 1990 having an issue data of Mar. 8, 1994 with inventor Lo which isincorporated by reference herein and may contain essential material forthe wireless location capabilities disclosed herein.

Still referring to the hypothesis evaluator 1228, it is important tonote that not all the above mentioned modules are required in allembodiments of the wireless location capabilities disclosed herein. Inparticular, the hypothesis analyzer 1332 may be unnecessary.Accordingly, in such an embodiment, the enhanced location hypothesesoutput by the context adjuster 1326 are provided directly to the mostlikelihood estimator 1344.

Control and Output Gating Modules

A fourth functional group of location engine 139 modules is the controland output gating modules which includes the location center controlsubsystem 1350, and the output gateway 1356. The location controlsubsystem 1350 provides the highest level of control and monitoring ofthe data processing performed by the location center 142. In particular,this subsystem performs the following functions:

-   -   (a) controls and monitors location estimating processing for        each target MS 140. Note that this includes high level exception        or error handling functions;    -   (b) receives and routes external information as necessary. For        instance, this subsystem may receive (via, e.g., the public        telephone switching network and Internet 468) such environmental        information as increased signal noise in a particular service        area due to increase traffic, a change in weather conditions, a        base station 122 (or other infrastructure provisioning), change        in operation status (e.g., operational to inactive);    -   (c) receives and directs location processing requests from other        location centers 142 (via, e.g., the Internet);    -   (d) performs accounting and billing procedures such as billing        according to MS location accuracy and the frequency with which        an MS is located;    -   (e) interacts with location center operators by, for example,        receiving operator commands and providing output indicative of        processing resources being utilized and malfunctions;    -   (f) provides access to output requirements for various        applications requesting location estimates. For example, an        Internet location request from a trucking company in Los Angeles        to a location center 142 in Denver may only want to know if a        particular truck or driver is within the Denver area.        Alternatively, a local medical rescue unit is likely to request        a precise a location estimate as possible.    -   Note that in FIG. 6, (a)-(d) above are, at least at a high        level, performed by utilizing the operator interface 1374

Referring now to the output gateway 1356, this module routes target MS140 location estimates to the appropriate location application(s). Forinstance, upon receiving a location estimate from the most likelihoodestimator 1344, the output gateway 1356 may determine that the locationestimate is for an automobile being tracked by the police and thereforemust be provided must be provided according to the particular protocol.

System Tuning and Adaptation: The Adaptation Engine

A fifth functional group of location engine 139 modules provides theability to enhance the MS locating reliability and/or accuracy of thewireless location capabilities disclosed herein by providing it with thecapability to adapt to particular operating configurations, operatingconditions and wireless signaling environments without performingintensive manual analysis of the performance of various embodiments ofthe location engine 139. That is, this functional group automaticallyenhances the performance of the location engine for locating MSs 140within a particular coverage area 120 using at least one wirelessnetwork infrastructure therein. More precisely, this functional groupallows the wireless location capabilities disclosed herein to adapt bytuning or optimizing certain system parameters according to locationengine 139 location estimate accuracy and reliability.

There are a number location engine 139 system parameters whose valuesaffect location estimation, and it is an aspect of the wireless locationcapabilities disclosed herein that the MS location processing performedshould become increasingly better at locating a target MS 140 not onlythrough building an increasingly more detailed model of the signalcharacteristics of location in the coverage area 120 such as discussedabove regarding the location signature data base 1320, but also byproviding automated capabilities for the location center processing toadapt by adjusting or “tuning” the values of such location center systemparameters.

Accordingly, the wireless location capabilities disclosed herein mayinclude a module, denoted herein as an “adaptation engine” 1382, thatperforms an optimization procedure on the location center 142 systemparameters either periodically or concurrently with the operation of thelocation center in estimating MS locations. That is, the adaptationengine 1382 directs the modifications of the system parameters so thatthe location engine 139 increases in overall accuracy in locating targetMSs 140. In one embodiment, the adaptation engine 1382 includes anembodiment of a genetic algorithm as the mechanism for modifying thesystem parameters. Genetic algorithms are basically search algorithmsbased on the mechanics of natural genetics.

Note that additional description of this aspect of the wireless locationcapabilities disclosed herein can be found in one of the following twocopending U.S. patent applications which are incorporated herein byreference: (a) “Location Of A Mobile Station” filed Nov. 24, 1999 havingapplication Ser. No. 09/194,367 whose inventors are D. J. Dupray and C.L. Karr, and (b) “A Wireless Location System For Calibrating MultipleLocation Estimators” filed Oct. 21, 1998 having application Ser. No.09/176,587 whose inventor is D. J. Dupray, wherein these copendingpatent applications may have essential material for the presentspecification. In particular, these copending patent applications mayhave essential material relating to the use of genetic algorithmimplementations for adaptively tuning system parameters of a particularembodiment of the wireless location capabilities disclosed herein.

Implementations of First Order Models

Further descriptions of various first order models 1224 are provided inthis section. However, it is important to note that these are merelyrepresentative embodiments of location estimators that are within thescope of the wireless location capabilities disclosed herein. Inparticular, two or more of the wireless location technologies describedhereinbelow may be combined to created additional First Order Models.For example, various triangulation techniques between a target MS 140and the base station infrastructure (e.g., time difference of arrival(TDOA) or time of arrival (TOA)), may be combined with an angle ofarrival (AOA) technique. For instance, if a single direct line of sightangle measurement and a single direct line of sight distance measurementdetermined by, e.g., TDOA or TOA can effectively location the target MS140. In such cases, the resulting First Order Models may be morecomplex. However, location hypotheses may generated from such modelswhere individually the triangulation techniques and the AOA techniqueswould be unable to generate effective location estimates.

Terrestrial Communication Station Offset (TCSO) First Order Models(e.g., TOA/TDOA/AOA)

As discussed in the Location Center Architecture Overview section hereinabove, TCSO models determine a presumed direction and/or distance (moregenerally, an offset) that a target MS 140 is from one or more basestations 122. In some embodiments of TCSO models, the target MS locationestimate(s) generated are obtained using radio signal analysistechniques that are quite general and therefore are not capable oftaking into account the peculiarities of the topography of a particularradio coverage area. For example, substantially all radio signalanalysis techniques using conventional procedures (or formulas) arebased on “signal characteristic measurements” such as:

(a) signal timing measurements (e.g., TOA and TDOA), and/or

(b) signal strength measurements.

Furthermore, such signal analysis techniques are likely predicated oncertain very general assumptions that can not fully account for signalattenuation and multipath due to a particular radio coverage areatopography.

Taking CDMA or TDMA base station network as an example, each basestation (BS) 122 is required to emit a constant signal-strength pilotchannel pseudo-noise (PN) sequence on the forward link channelidentified uniquely in the network by a pilot sequence offset andfrequency assignment. It is possible to use the pilot channels of theactive, candidate, neighboring and remaining sets, maintained in thetarget MS, for obtaining signal characteristic measurements (e.g., TOAand/or TDOA measurements) between the target MS 140 and the basestations in one or more of these sets.

Based on such signal characteristic measurements and the speed of signalpropagation, signal characteristic ranges or range differences relatedto the location of the target MS 140 can be calculated. Using TOA and/orTDOA ranges as exemplary, these ranges can then be input to either theradius-radius multilateration or the time difference multilaterationalgorithms along with the known positions of the corresponding basestations 122 to thereby obtain one or more location estimates of thetarget MS 140. For example, if there are, four base stations 122 in theactive set, the target MS 140 may cooperate with each of the basestations in this set to provide signal arrival time measurements.Accordingly, each of the resulting four sets of three of these basestations 122 may be used to provide an estimate of the target MS 140 asone skilled in the art will understand. Thus, potentially (assuming themeasurements for each set of three base stations yields a feasiblelocation solution) there are four estimates for the location of thetarget MS 140. Further, since such measurements and BS 122 positions canbe sent either to the network or the target MS 140, location can bedetermined in either entity.

Since many of the signal measurements utilized by embodiments of TCSOmodels are subject to signal attenuation and multipath due to aparticular area topography. Many of the sets of base stations from whichtarget MS location estimates are desired may result in either nolocation estimate, or an inaccurate location estimate.

Accordingly, some embodiments of TCSO FOMs may attempt to mitigate suchambiguity or inaccuracies by, e.g., identifying discrepancies (orconsistencies) between arrival time measurements and other measurements(e.g., signal strength), these discrepancies (or consistencies) may beused to filter out at least those signal measurements and/or generatedlocation estimates that appear less accurate. In particular, suchidentifying and filtering may be performed by, for example, an expertsystem residing in the TCSO FOM.

Another approach for enhancing certain location techniques such as TDOAor angle or arrival (AOA) is that of super resolution as disclosed inU.S. Pat. No. 5,890,068 (also referred to as the '068 patent herein)filed on Oct. 3, 1996 having an issue date of Mar. 30, 1999 withinventors Fattouche et. al. which is incorporated by reference hereinand which may contain essential material for the wireless locationcapabilities disclosed herein. Note that such super resolutiondetermines, for at least one of the base stations 122 (more generally,as disclosed in the '068 patent, a wireless “monitoring site”), one of:a distance, and a time difference of arrival between the target mobilestation and the base station, wherein said first technique estimates atime of arrival (TOA) of a received signal relative to a time referenceat each one of a plurality of wireless signal monitoring stations usingan inverse transform whose resolution is greater than Rayleighresolution. In particular, the following portions of the '068 patent areparticularly important: the Summary section, the Detailed Descriptionportion regarding FIGS. 12-17, and the section titled “Description OfThe Preferred Embodiments Of The Invention.”

Another approach, regardless of the FOM utilized, for mitigating suchambiguity or conflicting MS location estimates is particularly novel inthat each of the target MS location estimates is used to generate alocation hypothesis regardless of its apparent accuracy. Accordingly,these location hypotheses are input to an embodiment of the contextadjuster 1326. In particular, in one context adjuster 1326 embodimenteach location hypothesis is adjusted according to past performance ofits generating FOM 1224 in an area of the initial location estimate ofthe location hypothesis (the area, e.g., determined as a function ofdistance from this initial location estimate), this alternativeembodiment adjusts each of the location hypotheses generated by a firstorder model according to a past performance of the model as applied tosignal characteristic measurements from the same set of base stations122 as were used in generating the location hypothesis. That is, insteadof only using only an identification of the first order model (i.e., itsFOM_ID) to, for example, retrieve archived location estimates generatedby the model in an area of the location hypothesis' estimate (whendetermining the model's past performance), the retrieval retrieves thearchived location estimates that are, in addition, derived from thesignal characteristics measurement obtained from the same collection ofbase stations 122 as was used in generating the location hypothesis.Thus, the adjustment performed by this embodiment of the contextadjuster 1326 adjusts according to the past performance of the distancemodel and the collection of base stations 122 used.

Note in one embodiment, such adjustments can also be implemented using aprecomputed vector location error gradient field. Thus, each of thelocation error vectors (as determined by past performance for the FOM)of the gradient field has its starting location at a location previouslygenerated by the FOM, and its vector head at a corresponding verifiedlocation where the target MS 140 actually was. Accordingly, for alocation hypothesis of an unknown location, this embodiment determinesor selects the location error vectors having starting locations within asmall area (e.g., possibly of a predetermined size, but alternatively,dependent on the density of the location error vector starting locationsnearby to the location hypothesis) of the location hypothesis.Additionally, the determination or selection may also be based upon asimilarity of signal characteristics also obtained from the target MS140 being located with signal characteristics corresponding to thestarting locations of location error vectors of the gradient field. Forexample, such sign characteristics may be, e.g., time delay/signalstrength multipath characteristics.

Angle of Arrival First Order Model

Various mobile station location estimating models can be based on theangle of arrival (AOA) of wireless signals transmitted from a target MS140 to the base station infrastructure as one skilled in the art willunderstand. Such AOA models (sometimes also referred to as direction ofarrival or DOA models) typically require precise angular measurements ofthe wireless signals, and accordingly utilize specialized antennas atthe base stations 122. The determined signal transmission angles aresubject to multipath aberrations. Therefore, AOA is most effective whenthere is an unimpeded line-of-sight simultaneous transmission betweenthe target MS 140 and at least two base stations 122.

TCSO (Grubeck) FOM with Increased Accuracy Via Multiple MS Transmissions

Another TCSO first order model 1224, denoted the Grubeck model (FOM)herein, is disclosed in U.S. Pat. No. 6,009,334 filed Nov. 26, 1997 andissued Dec. 28, 1999 having Grubeck, Fischer, and Lundqvist asinventors, this patent being fully incorporated herein by reference. TheGrubeck model includes a location estimator for determining moreaccurately the distance between a wireless receiver at (RX), e.g., aCMRS fixed location communication station (such as a BS 122) and atarget MS 140, wherein wireless signals are repeatedly transmitted fromthe target MS 140 and may be subject to multipath. An embodiment of theGrubeck model may be applied to TOA, TDOA, and/or AOA wirelessmeasurements. For the TOA case, the following steps are performed:

-   -   (a) transmitting “M” samples s_(i)1<=|<=M of the same wireless        signal from, e.g., the target MS 140 to the RX. Preferably M is        on the order of 50 to 100 (e.g., 70) wireless signal bursts,        wherein each such burst contains a portion having an identical        known contents of bits (denoted a training sequence). However,        note that a different embodiment can use (e.g., 70) received        bursts containing different (non-identical) information, but        information still known to the RX;    -   (b) receiving the “M” signal samples s_(i) along with multipath        components and noise at, e.g., RX;    -   (c) for each of the received “M” samples s_(i), determining at        the RX an estimated channel power profile (CPPi). Each CPPi is        determined by first determining, via a processor at the RX, a        combined correlation response (“Channel Impulse Response” or        CIRi) of a small number of the bursts (e.g., 5) by correlating        each burst with its known contents. Accordingly; the squared        absolute value of the CIRi is the “estimated channel power        profile” or CPPi;    -   (d) (randomly) selecting “N” (e.g., 10) out of the “M” received        samples;    -   (e) performing incoherent integration of the CPPi for the “N”        samples selected, which results in an integrated signal, i.e.,        one integrated channel power profile_ICPP(Ni);    -   (f) determining if the signal-to-noise quality of the ICPP(Ni)        is greater than or equal to a predetermined threshold value, and        if not, improving the signal-to-noise quality of ICPP(Ni) as        required, by redoing the incoherent integration with        successively one additional received sample CPPi until the        signal-to-noise quality of the ICPP(Ni) is greater than or equal        to the predetermined threshold value;    -   (g) determining the TOA(i), including the case of determining        TOA(i) from the maximum signal amplitude;    -   (h) entering the determined TOA(i) value into a diagram that        shows a frequency of occurrence as a function of TOA(i);    -   (i) repeating the whole procedure “X” times by selecting a new        combination of “N” out of “M” samples, which results in “X”        additional points in the frequency of occurrence diagram;    -   (j) reading the minimum value TOA(min) as the time value having        “z” of all occurrences with higher TOA(i) values and “1-z” of        all occurrences with lower TOA(i) values, where z>0.7.

As mentioned above, an embodiment of the Grubeck FOM may also beprovides for TDOA and/or AOA wireless location techniques, wherein asimilar incoherent integration may be performed.

Note that a Grubeck FOM may be particularly useful for locating a targetMS 140 in a GSM wireless network.

TCSO (Parl) FOM Using Different Tones and Multiple Antennas at BSs 122

A first order model 1224, denoted the Parl model herein, issubstantially disclosed in U.S. Pat. No. 5,883,598 (denoted the '598Patent herein) filed Dec. 15, 1995 and issued Mar. 16, 1999 having Parl,Bussgang, Weitzen and Zagami as inventors, this patent being fullyincorporated herein by reference. The Parl FOM includes a system forreceiving representative signals (denoted also “locating signal(s)”)from the target MS 140 via, e.g., base stations 122 and subsequentlycombining information regarding the amplitude and phase of the MStransmitted signals received at the base stations to determine theposition of the target MS 140. In one embodiment, the Parl model usesinput from a locating signal having two or more single-frequency tones,as one skilled in the art will understand. Moreover, at least some ofthe base stations 122 preferably include at least two antennas spacedfrom each other by a distance between a quarter wavelength and severalwavelengths of the wireless locating signals received from the target MS140. Optionally, another antenna vertically above or below the two ormore antennas also spaced by a distance of between a quarter wavelengthand several wavelengths can be used where elevation is also beingestimated. The base stations 122 sample locating signals from the targetMS 140. The locating signals include tones that can be at differentfrequencies. The tones can also be transmitted at different times, or,in an alternative embodiment, they can be transmitted simultaneously.Because, in one embodiment, only single-frequency tones are used as thelocating signal instead of modulated signals, substantial transmissioncircuitry may be eliminated. The Parl FOM extracts information from eachrepresentative signal received from a target MS 144, wherein at leastsome of the extracted information is related to the amplitude and phaseof the received signal.

In one embodiment of a Parl FOM, related to the disclosure in the '598Patent, when the locations of the BSs 122 are known, and the directionfrom any two of the BSs 122 to the target MS 140, the MS's location canbe initially (roughly) determined by signal direction findingtechniques. For example, an estimate of the phase difference between thesignals at a pair of antennas at any BS 122 (having two such antennas)can lead to the determination of the angle from the base station to thetarget MS 140, and thus, the determination of the target MS direction.Subsequently, an enhanced location of the target MS 140 is computeddirectly from received target MS signal data using an ambiguity functionA(x,y) described in the '598 Patent, wherein for each point at x,y, theambiguity function A(x,y) depends upon the probability that the MS islocated at the geolocation represented by (x,y). Essentially the ParlFOM combines angle of arrival related data and TDOA related data forobtaining an optimized estimate of the target MS 140. However, itappears that independent AOA and TDOA MS locations are not used indetermining a resulting target MS location (e.g., without the need forprojecting lines at angles of arrival or computing the intersection ofhyperbolas defined by pairs of base stations). Instead, the Parl FOMestimates the target MS's location by minimizing a joint probability oflocation related errors. In particular, such minimization may use themean square error, and the location (x, y) at which minimization occursis taken as the estimate of the target MS 140. In particular, theambiguity function A(x,y) defines the error involved in a positiondetermination for each point in a geolocation Cartesian coordinatesystem. The Parl model optimizes the ambiguity function to select apoint x,y at which the associated error is minimized. The resultinglocation for (x, y) is taken as the estimate of the location of thetarget MS 140. Any of several different optimization procedures can beused to optimize the ambiguity function A(x,y). E.g., a first roughestimate of the target MS's location may be obtained by directionfinding (as discussed above). Next, six points x,y may be selected thatare in close proximity to the estimated point. The ambiguity functionA(x,y) is solved for each of the x,y points to obtain six values. Thesix computed values are then used to define a parabolic surface. Thepoint x,y at which the maximum value of the parabolic surface occurs isthen taken as the estimate of the target MS 140. However, otheroptimization techniques may also be used. For example, a standardtechnique such as an iterative progression through trial and error toconverge to the maximum can be used. Also, gradient search can be usedto optimize the ambiguity function. In the case of three-dimensionallocation, the two-dimensional ambiguity function A(x,y) is extended to athree-dimensional function A(x, y, z). As in the two-dimensional case,the ambiguity function may be optimized to select a point x, y, z as thebest estimate of the target MS's location in three dimensions. Again,any of several known optimization procedures, such as iterativeprogression through trial and error, gradient search, etc., can be usedto optimize the ambiguity function.

TCSO FOM Using TDOA/AOA Measurements From an MBS 148 and/or an LBS 152

It is believed that from the location center/gateway 142 architectureand from the architecture of the mobile station location subsystem(described in a separate section hereinbelow) that target MS 140location related information can be obtained from an MBS 148 and/or oneor more LBSs 152. Moreover, such location related information can besupplied to any FOM 1224 that is able to accept such information asinput. Thus, pattern recognition and adaptive FOMs may accept suchinformation. However, to provide an alternative description of how MSlocation related information from an MBS and/or LBS may be used,reference is made to U.S. Pat. No. 6,031,490 (denoted the '490 Patentherein) filed Dec. 23, 1997 and issued Feb. 29, 2000 having Forssen,Berg and Ghisler as inventors, this patent being fully incorporatedherein by reference. A TCSO FOM (denoted the FORSSEN FOM herein) usingTDOA/AOA is disclosed in the '490 Patent.

The FORSSEN FOM includes a location estimator for determining the TimeDifference of Arrival (TDOA) of the position of a target MS 140, whichis based on Time of Arrival (TOA) and/or AOA measurements. This FOM usesdata received from “measuring devices” provided within a wirelesstelecommunications network. The measuring devices measure TOA on demandand (optionally) Direction of Arrival (DOA), on a digital uplink timeslot or on digital information on an analog uplink traffic channel inone or more radio base stations. The TOA and DOA information and thetraffic channel number are reported to a Mobile Services SwitchingCenter (MSC), which obtains the identity of the target MS 140 from thetraffic channel number and sends the target MS 140 identity and TOA andDOA measurement information to a Service Node (e.g., location center142) of the network. The Service Node calculates the position of thetarget MS 140 using the TOA information (supplemented by the DOAinformation when available). Note, that the FORSSEN model may utilizedata from a second mobile radio terminal that is colocated on a mobileplatform (auto, emergency vehicle, etc.) with one of the radio basestations (e.g., MBS 148), which can be moved into relatively closeproximity with the target MS 140. Consequently, by moving one of theradio base stations (MBSs) close to the region of interest (near thetarget MS 140), the position determination accuracy is significantlyimproved.

Note that the '490 Patent also discloses techniques for rising thetarget MS's transmission power for thereby allowing wireless signalsfrom the target MS to be better detected by distant BSs 122.

Coverage Area First Order Model

Radio coverage area of individual base stations 122 may be used togenerate location estimates of the target MS 140. Although a first ordermodel 1224 based on this notion may be less accurate than othertechniques, if a reasonably accurate RF coverage area is known for each(or most) of the base stations 122, then such a FOM (denoted hereinafteras a “coverage area first order model” or simply “coverage area model”)may be very reliable. To determine approximate maximum radio frequency(RF) location coverage areas, with respect to BSs 122, antennas and/orsector coverage areas, for a given class (or classes) of (e.g., CDMA orTDMA) mobile station(s) 140, location coverage should be based on anMS's ability to adequately detect the pilot channel, as opposed toadequate signal quality for purposes of carrying user-acceptable trafficin the voice channel. Note that more energy is necessary for trafficchannel activity (typically on the order of at least −94 to −104 dBmreceived signal strength) to support voice, than energy needed to simplydetect a pilot channel's presence for location purposes (typically amaximum weakest signal strength range of between −104 to −110 dBm), thusthe “Location Coverage Area” will generally be a larger area than thatof a typical “Voice Coverage Area”, although industry studies have foundsome occurrences of “no-coverage” areas within a larger covered area

The approximate maximum RF coverage area for a given sector of (moregenerally angular range about) a base station 122 may be represented asa set of points representing a polygonal area (potentially with, e.g.,holes therein to account for dead zones and/or notches). Note that ifsuch polygonal RF coverage area representations can be reliablydetermined and maintained over time (for one or more BS signal powerlevel settings), then such representations can be used in providing aset theoretic or Venn diagram approach to estimating the location of atarget MS 140. Coverage area first order models utilize such anapproach.

One embodiment, a coverage area model utilizes both the detection andnon-detection of base stations 122 by the target MS 140 (conversely, ofthe MS by one or more base stations 122) to define an area where thetarget MS 140 may likely be. A relatively straightforward application ofthis technique is to:

-   -   (a) find all areas of intersection for base station RF coverage        area representations, wherein: (i) the corresponding base        stations are on-line for communicating with MSs 140; (ii) the RF        coverage area representations are deemed reliable for the power        levels of the on-line base stations; (iii) the on-line base        stations having reliable coverage area representations can be        detected by the target MS; and (iv) each intersection must        include a predetermined number of the reliable RF coverage area        representations (e.g., 2 or 3); and    -   (b) obtain new location estimates by subtracting from each of        the areas of intersection any of the reliable RF coverage area        representations for base stations 122 that can not be detected        by the target MS.

Accordingly, the new areas may be used to generate location hypotheses.

Satellite Signal Triangulation First Order Models

As mentioned hereinabove, there are various satellite systems that maybe used to provide location estimates of a target MS 140 (e.g., GPS,GLONASS, LEOs, and MEOs). In many cases, such location estimates can bevery accurate, and accordingly such accuracy would be reflected in thewireless location capabilities disclosed herein by relatively highconfidence values for the location hypotheses generated from such modelsin comparison to other FOMs. However, it may be difficult for the targetMS 140 to detect and/or lock onto such satellite signals sufficientlywell to provide a location estimate. For example, it may be veryunlikely that such satellite signals can be detected by the MS 140 inthe middle of high rise concrete buildings or parking structures havingvery reduced exposure to the sky.

Hybrid Satellite and TCSO FOMs

A first order model 1224, denoted the WAITERS FOM herein, is disclosedin U.S. Pat. No. 5,982,324 filed May 14, 1998 and issued Nov. 9, 1999having Watters, Strawczynski, and Steer as inventors, this patent beingfully incorporated herein by reference. The WAITERS FOM includes alocation estimator for determining the location of a target MS 140 usingsatellite signals to the target MS 140 as well as delay in wirelesssignals communicated between the target MS and base stations 122. Forexample, aspects of global positioning system (GPS) technology andcellular technology are combined in order to locate a target MS 140. TheWATTERS FOM may be used to determine target MS location in a wirelessnetwork, wherein the network is utilized to collect differential GPSerror correction data, which is forwarded to the target MS 140 via thewireless network. The target MS 140 (which includes a receiver R forreceiving non-terrestrial wireless signals from, e.g., GPS, or othersatellites, or even airborne craft) receives this data, along with GPSpseudoranges using its receiver R, and calculates its position usingthis information. However, when the requisite number of satellites arenot in view of the MS 140, then a pseudosatellite signal, broadcast froma BS 122 of the wireless network, is received by the target MS 140 andprocessed as a substitute for the missing satellite signal.Additionally, in at least some circumstances, when the requisite numberof satellites (more generally, non-terrestrial wireless transmitters)are not detected by the receiver R, then the target MS's location iscalculated using the wireless network infrastructure via TDOA/TOA withthe BSs 122 of the network. When the requisite number of satellites(more generally, non-terrestrial wireless transmitters) are againdetected by the receiver R, then the target MS is again calculated usingwireless signals from the non-terrestrial wireless transmitters.Additionally, the WATTERS FOM may use wireless signals already beingtransmitted from base stations 122 to the target MS 140 in wirelessnetwork to calculate a round trip time delay, from which a distancecalculation between the base station and the target MS can be made. Thisdistance calculation substitutes for a missing non-terrestrialtransmission signal.

Location Base Station First Order Model

In the location base station (LBS) model (FOM 1224), a database isaccessed which contains electrical, radio propagation and coverage areacharacteristics of each of the location base stations in the radiocoverage area. The LBS model is an active model, in that it can probe orexcite one or more particular LBSs 152 in an area for which the targetMS 140 to be located is suspected to be placed. Accordingly, the LBSmodel may receive as input a most likely target MS 140 location estimatepreviously output by the location engine 139 of the wireless locationcapabilities disclosed herein, and use this location estimate todetermine which (if any) LBSs 152 to activate and/or deactivate forenhancing a subsequent location estimate of the target MS. Moreover, thefeedback from the activated LBSs 152 may be provided to other FOMs 1224,as appropriate, as well as to the LBS model. However, it is an importantaspect of the LBS model that when it receives such feedback, it mayoutput location hypotheses having relatively small target MS 140location area estimates about the active LBSs 152 and each such locationhypothesis also has a high confidence value indicative of the target MS140 positively being in the corresponding location area estimate (e.g.,a confidence value of 0.9 to +1), or having a high confidence valueindicative of the target MS 140 not being in the corresponding locationarea estimate (i.e., a confidence value of −0.9 to −1). Note that insome embodiments of the LBS model, these embodiments may havefunctionality similar to that of the coverage area first order modeldescribed above. Further note that for LBSs within a neighborhood of thetarget MS wherein there is a reasonable chance that with movement of thetarget MS may be detected by these LBSs, such LBSs may be requested toperiodically activate. (Note, that it is not assumed that such LBSs havean on-line external power source; e.g., some may be solar powered).Moreover, in the case where an LBS 152 includes sufficient electronicsto carry voice communication with the target MS 140 and is the primaryBS for the target MS (or alternatively, in the active or candidate set),then the LBS model will not deactivate this particular LBS during itsprocedure of activating and deactivating various LBSs 152.

Stochastic First Order Model

The stochastic first order models may use statistical predictiontechniques such as principle decomposition, partial least squares,partial least squares, or other regression techniques for predicting,for example, expected minimum and maximum distances of the target MSfrom one or more base stations 122, e.g., Bollenger Bands. Additionally,some embodiments may use Markov processes and Random Walks (predictedincremental MS movement) for determining an expected area within whichthe target MS 140 is likely to be. That is, such a process measures theincremental time differences of each pilot as the MS moves forpredicting a size of a location area estimate using past MS estimatessuch as the verified location signatures in the location signature database 1320.

Pattern Recognition and Adaptive First Order Models

It is a particularly important aspect of the wireless locationcapabilities disclosed herein to provide:

-   -   (a) one or more FOMs 1224 that generate target MS 140 location        estimates by using pattern recognition or associativity        techniques, and/or    -   (b) one or more FOMs 1224 that are adaptive or trainable so that        such FOMs may generate increasingly more accurate target MS        location estimates from additional training.

Statistically Based Pattern Recognition First Order Models

Regarding FOMs 1224 using pattern recognition or associativitytechniques, there are many such techniques available. For example, thereare statistically based systems such as “CART” (acronym forClassification and Regression Trees) by ANGOSS Software InternationalLimited of Toronto, Canada that may be used for automatically fordetecting or recognizing patterns in data that were not provided (andlikely previously unknown). Accordingly, by imposing a relatively finemesh or grid of cells of the radio coverage area, wherein each cell isentirely within a particular area type categorization, such as thetransmission area types (discussed in the section, “Coverage Area: AreaTypes And Their Determination” above), the verified location signatureclusters within the cells of each area type may be analyzed for signalcharacteristic patterns. Accordingly, if such a characteristic patternis found, then it can be used to identify one or more of the cells inwhich a target MS is likely to be located. That is, one or more locationhypotheses may be generated having target MS 140 location estimates thatcover an area having the identified cells wherein the target MS 140 islikely to be located. Further note that such statistically based patternrecognition systems as “CART” include software code generators forgenerating expert system software embodiments for recognizing thepatterns detected within a training set (e.g., the verified locationsignature clusters).

A related statistical pattern recognition FOM 1224 is also disclosed inU.S. Pat. No. 6,026,304, filed Jan. 8, 1997 and issued Feb. 15, 2000,having Hilsenrath and Wax as inventors, this patent (denoted theHilsenrath patent herein) being incorporated herein fully by reference.An embodiment of a FOM 1224 based on the disclosure of the Hilsenrathpatent is referred to herein as the Hilsenrath FOM. The Hilsenrath FOMincludes a wireless location estimator that locates a target MS 140using measurements of multipath signals in order to accurately determinethe location of the target MS 140. More particularly, to locate thetarget MS 140, the Hilsenrath FOM uses wireless measurements of both adirect signal transmission path and multipath transmission signals fromthe MS 140 to a base station 122 receiver. The wireless signals from thetarget MS 140 arrive at and are detected by an antenna array of thereceiver at the BS 122, wherein the antenna array includes a pluralityof antennas. A signal signature (e.g., an embodiment of a locationsignature herein) for this FOM may be derived from any combination ofamplitude, phase, delay, direction, and polarization information of thewireless signals transmitted from the target MS 140 to the base station122 receiver. The Hilsenrath FOM 1224 determines a signal signature froma signal subspace of a covariance matrix. In particular, for p antennasincluded in the base station receiver, these antennas are used toreceive complex signal envelopes x.₁(t), x.₂(t), . . . , x._(p)(t),respectively, which are conventionally grouped together to form ap-dimensional array vector x(t)=[x₁(t), x₂(t), . . . , x._(p)(t)]^(T).The signal subspace may be determined from a collection of M such arrayvectors x(t) by several techniques. In one such technique, the outerproducts of the M vectors are added together to form a p×p signalcovariance matrix, R=1/M[x(t₁)x(t₁)^(H)+ . . . +x(t_(M))x(t_(M))^(H)].The eigenvalues of R whose magnitudes exceed a predetermined thresholddetermine a set of dominant eigenvectors. The signal subspace is thespace spanned by these dominant eigenvectors. The signal signature iscompared to a database of calibrated signal signatures and correspondinglocations (e.g., an embodiment of the location signature data base1320), wherein the signal signatures in the database includerepresentations of the signal subspaces (such as the dominanteigenvectors of the covariance matrices. Accordingly, a location whosecalibrated signature best matches the signal signature of the target MS140 is selected as the most likely location of the target MS 140. Notethat the database of calibrated signal signatures and correspondingverified locations is generated by a calibration procedure in which acalibrating MS 140 transmits location data derived from a co-located GPSreceiver to the base stations 122. Thus, for each of a plurality oflocations distributed through a service area, the location hasassociated therewith: the (GPS or verified) location information and thecorresponding signal signature of the calibrating MS 140.

Accordingly, the location of a target MS 140 in the service area may bedetermined as follows. Signals originating from the target MS 140 at anunknown location are received at a base station 122. A signal processor,e.g., at the base station 122, then determines the signal signature asdescribed above. The signal signature is then compared with thecalibrated signal signatures stored in the above described embodiment ofthe location signature database 1320 during the calibration procedure.Using a measure of difference between subspaces (e.g., an angle betweensubspaces), a set of likely locations is selected from this locationsignature database embodiment. These selected likely locations are thoselocations whose associated calibrated signal signatures differ by lessthan a minimum threshold value from the target MS 140 signal signature.The difference measure is further used to provide a correspondingmeasure of the probability that each of the selected likely locations isthe actual target MS location. Moreover, for one or more of the selectedlikely location, the corresponding measure may be output as theconfidence value for a corresponding location hypothesis output by aHilsenrath FOM 1224.

Thus, an embodiment of the wireless location capabilities disclosedherein using such a Hilsenrath FOM 1224 performs the following steps(a)-(d):

-   -   (a) receiving at an antenna array provided at one of the base        stations 122, signals originating from the target MS 140,        wherein the signals comprise p-dimensional array vectors sampled        from p antennas of the array;    -   (b) determining from the received signals, a signal signature,        wherein the signal signature comprises a measured subspace,        wherein the array vectors x(t) are approximately confined to the        measured subspace;    -   (c) comparing the signal signature to previously obtained (and        similarly computed) signal signatures, wherein each of the        previously obtained signal signatures, SS, has associated        therewith corresponding location data verifying the location        where SS was obtained, wherein this step of comparing comprises        substep of calculating differences between: (i) the measured        subspace, and (ii) a similarly determined subspace for each of a        plurality of the previously obtained signal signatures; and    -   (d) selecting from the previously obtained signal signatures a        most likely signal signature and a corresponding most likely        location of the target MS 140 by using the calculated        differences;

Note that regardless of the reliability some FOMs as described here maynot be exceedingly accurate, but may be very reliable. Thus, since anaspect of at least some embodiments of the wireless locationcapabilities disclosed herein is to use a plurality of MS locationtechniques (FOMs) for generating location estimates and to analyze thegenerated estimates (likely after being adjusted) to detect patterns ofconvergence or clustering among the estimates, even large MS locationarea estimates may be useful. For example, it can be the case that fourdifferent and relatively large MS location estimates, each having veryhigh reliability, have an area of intersection that is acceptablyprecise and inherits the very high reliability from each of the large MSlocation estimates from which the intersection area was derived.

Note, that another statistically based FOM 1224 may be provided whereinthe radio coverage area is decomposed substantially as above, but inaddition to using the signal characteristics for detecting useful signalpatterns, the specific identifications of the base station 122 providingthe signal characteristics may also be used. Thus, assuming there is asufficient density of verified location signature clusters in some ofthe mesh cells so that the statistical pattern recognizer can detectpatterns in the signal characteristic measurements, an expert system maybe generated that outputs a target MS 140 location estimate that mayprovide both a reliable and accurate location estimate of a target MS140.

Adaptive/Trainable First Order Models

The term adaptive is used to describe a data processing component thatcan modify its data processing behavior in response to certain inputsthat are used to change how subsequent inputs are processed by thecomponent. Accordingly, a data processing component may be “explicitlyadaptive” by modifying its behavior according to the input of explicitinstructions or control data that is input for changing the component'ssubsequent behavior in ways that are predictable and expected. That is,the input encodes explicit instructions that are known by a user of thecomponent. Alternatively, a data processing component may be “implicitlyadaptive” in that its behavior is modified by other than instructions orcontrol data whose meaning is known by a user of the component. Forexample, such implicitly adaptive data processors may learn by trainingon examples, by substantially unguided exploration of a solution space,or other data driven adaptive strategies such as statistically generateddecision trees. Accordingly, it is an aspect of the wireless locationcapabilities disclosed herein to utilize not only explicitly adaptive MSlocation estimators within FOMs 1224, but also implicitly adaptive MSlocation estimators. In particular, artificial neural networks (alsodenoted neural nets and ANNs herein) are used in some embodiments asimplicitly adaptive MS location estimators within FOMs. Thus, in thesections below, neural net architectures and their application tolocating an MS is described.

Artificial Neural Networks For MS Location

Artificial neural networks may be particularly useful in developing oneor more first order models 1224 for locating an MS 140, since, forexample, ANNs can be trained for classifying and/or associativelypattern matching of various RF signal measurements such as the locationsignatures. That is, by training one or more artificial neural netsusing RF signal measurements from verified locations so that RF signaltransmissions characteristics indicative of particular locations areassociated with their corresponding locations, such trained artificialneural nets can be used to provide additional target MS 140 locationhypotheses. Moreover, it is an aspect of the wireless locationcapabilities disclosed herein that the training of such artificialneural net based FOMs (ANN FOMs) is provided without manual interventionas will be discussed hereinbelow. Additional description of this aspectof the wireless location capabilities disclosed herein can be found inthe copending U.S. patent application titled “Location Of A MobileStation” filed Nov. 24, 1999 having application Ser. No. 09/194,367whose inventors are D. J. Dupray and C. L. Karr, which is incorporatedherein by reference and wherein this copending patent application mayhave essential material for the wireless location capabilities disclosedherein. In particular, this copending patent application may haveessential material relating to the use of ANNs as mobile stationlocation estimators 1224.

Other First Order Models

U.S. Pat. No. 5,390,339 (339 patent) filed Oct. 23, 1991 having an issuedate of Feb. 14, 1995 with inventor being Bruckert et. al. providesnumber of embodiments of wireless location estimators for estimating thelocation of a “remote unit.” In particular, various location estimatorembodiments are described in relation to FIGS. 1B and 2B therein. Thelocation estimators in the '339 patent are, in general, directed todetermining weighted or adjusted distances of the “remote unit” (e.g.,MS 140) from one or more “transceivers” (e.g., base stations 122). Thedistances are determined using signal strength measurements of wirelesssignals transmitted between the “remote unit” and the “transceivers.”However, adjustments are in the signal strengths according to varioussignal transmission anomalies (e.g., co-channel interference),impairments and/or errors. Additionally, a signal RF propagation modelmay be utilized, and a likelihood of the “remote unit” being in thedesignated coverage areas (cells) of particular transceivers (e.g., basestations 122) is determined using probabilistic techniques such asposteriori probabilities. Accordingly, the Bruckert '339 patent is fullyincorporated by reference herein and may contain essential material forthe wireless location capabilities disclosed herein.

U.S. Pat. No. 5,570,412 (412 patent) filed Sep. 28, 1994 having an issuedate of Oct. 29, 1996 with inventors LeBlanc et. al. provides furtherembodiments of wireless location estimators that may be used as FirstOrder Models 1224. The location estimating techniques of the LeBlanc'412 patent are described with reference to FIG. 8 and succeedingfigures therein. Ata high level, wireless location techniques of the'412 patent can be characterized by the following quote therefrom:

-   -   “The location processing of the wireless location capabilities        disclosed herein focuses on the ability to predict and model RF        contours using actual RF measurements, then performing data        reduction techniques such as curve fitting technique, Bollinger        Bands, and Genetic Algorithms, in order to locate a mobile unit        and disseminate its location.”        Accordingly, the LeBlanc '412 patent is fully incorporated by        reference herein and may contain essential material for the        wireless location capabilities disclosed herein.

U.S. Pat. No. 5,293,645 (645 patent) filed Oct. 4, 1991 having an issuedate of Mar. 8, 1994 with inventor Sood. provide further embodiments ofwireless location estimators that may be used as First Order Models1224. In particular, the '645 patent describes wireless locationestimating techniques using triangulations or other geographicalintersection techniques. Further, one such technique is described incolumn 6, line 42 through column 7, line 7. Accordingly, the Sood '645patent is fully incorporated by reference herein and may containessential material for the wireless location capabilities disclosedherein.

U.S. Pat. No. 5,293,642 (642 patent) filed Dec. 19, 1990 having an issuedate of Mar. 8, 1994 with inventor Lo provide further embodiments ofwireless location estimators that may be used as First Order Models1224. In particular, the '642 patent determines a correspondingprobability density function (pdf) about each of a plurality of basestations in communication with the target MS 140. That is, uponreceiving wireless signal measurements from the transmissions betweenthe target MS 140 and base stations 122, for each BS 122, acorresponding pdf is obtained from prior measurements of a particularwireless signal characteristic at locations around the base station.Subsequently, a most likely location estimation is determined from ajoint probability density function of the individual base stationprobability density functions. Further description can be found in theDescription Of The Preferred Embodiment section of the '642 patent.Accordingly, the Lo '642 patent is incorporated by reference herein andmay contain essential material for the wireless location capabilitiesdisclosed herein.

Hybrid First Order Models Time Difference of Arrival and Timing AdvanceFOM

A first order model 1224 denoted the Yost model herein. The Yost modelincludes a location estimator that uses a combination of Time Differenceof Arrival (TDOA) and Timing Advance (TA) location determiningtechniques for determining the location of a target MS 140, whereinthere are minor modifications to a telecommunication network such as aCMRS. The hybrid wireless location technique utilized by this locationestimator uses TDOA measurements and TA measurements to obtainsubstantially independent location estimates of the target MS 140,wherein the TDOA measurements determine hyperbolae MS loci, about basestations 122 communicating (uni or bi-directionally) with the target MS,and the TA measurements determine circles about the base stations 122.Accordingly, an enhanced location estimate of the MS 140 can be obtainedby using a least squares (or other statistical technique), wherein theleast-squares technique determines a location for the MS between thevarious curves (hyperbolae and circles) that best approximates a pointof intersection. Note that TA is used in all Time Division MultipleAccess (TDMA) systems as one skilled in the art will understand, andmeasurements of TA can provide a measurement of the distance of the MSfrom a TDMA communication station in communication with the target MS140. The Yost model is disclosed in U.S. Pat. No. 5,987,329 ('329Patent) filed Jul. 30, 1997 and issued Nov. 16, 1999 having Yost andPanchapakesan as inventors, this patent being fully incorporated hereinfully by reference to thereby further describe the Yost model. Thefollowing quote from the '329 Patent describes an important aspect ofthe Yost model:

-   -   “Furthermore, the combination of TA and TDOA allows resolution        of common ambiguities suffered by either technique separately.        For example, in FIG. 5 a situation involving three base stations        24 (A, B and C as described, the latter being visible in the        figure) is represented along with the resultant two hyperbolas        AB and AC (and redundant hyperbola BC) for a TDOA position        determination of the mobile M. FIG. 5 is a magnified view of the        mobile terminal M location showing the nearby base stations and        the nearby portions at the curves. It should be understood that,        in this case, using TDOA alone, there are two possible        solutions, where the hyperbolae cross. The addition of the TA        circles (dashed curves) will allow the ambiguous solutions,        which lie at different TA from all three base stations, to be        clearly resolved without the need for additional base station 24        measurements.”

As an aside note that a timing advance (TA) first order model may beprovided as a separate FOM independent from the TDOA portion of the Yostmodel. Thus, if an embodiment of the wireless location capabilitiesdisclosed herein includes both a TA FOM and a TDOA FOM, then themultiple location estimator architecture of the wireless locationcapabilities disclosed herein may substantially include the Yost modelwhenever the TA FOM and TDOA FOM are both activated for a same locationinstance of a target MS 140. However, it is an aspect of the wirelesslocation capabilities disclosed herein to also activate such a TA FOMand a TDOA FOM asynchronously from one another.

Satellite and Terrestrial Base Station Hybrid FOM

A first order model 1224, denoted the Sheynblat model (FOM) herein, isdisclosed in U.S. Pat. No. 5,999,124 (denoted the '124 Patent herein)filed Apr. 22, 1998 and issued Dec. 7, 1999 having Sheynblat as theinventor, this patent being fully incorporated herein by reference TheSheynblat FOM provides a location estimator for processing target MS 140location related information obtained from: (a) satellite signals of asatellite positioning system (denoted SPS in the '124 Patent) (e.g., GPSor GLONASS, LEO positioning satellites, and/or MEO positioningsatellites), and (b) communication signals transmitted in theterrestrial wireless cellular network of BSs 122 for a radio coveragearea, e.g., coverage area 120 (FIG. 4), wherein there is two-waywireless communication between the target MS 140 and the BSs. In oneembodiment of the Sheynblat FOM, the location related informationobtained from the satellite signals includes a representation of a timeof travel of SPS satellite signals from a SPS satellite to acorresponding SPS receiver operatively coupled to (and co-located with)the target MS 140 (such “time of travel” is referred to as a pseudorangeto the SPS satellite). Additionally for this embodiment, the locationrelated information obtained from the communication signals in thewireless cellular network includes time of travel related informationfor a message in the communication signals between a BS 122 transceiverand the target MS 140 (this second “time of travel” related informationis referred to as a cellular pseudorange). Accordingly, variouscombinations of pseudoranges to SPS satellites, and cellularpseudoranges can be used to determine a likely location of the target MS140. As an example, if the target MS 140 (enhanced with a SPS receiver)can receive SPS satellite signals from one satellite, and additionally,the target MS is also in wireless communication (or can be in wirelesscommunication) with two BSs 122, then three pseudoranges may be obtainedand used to determine the position of the target MS by, e.g.,triangulation. Of course, other combinations are possible fordetermining a location of the target MS 140, e.g., pseudoranges to twoSPS satellites and one cellular pseudorange. Additionally, varioustechniques may be used to mitigate the effects of multipath on thesepseudoranges. For example, since it is typical for the target MS 140 todetect (or be detected by) a plurality of BSs 122, a correspondingplurality of cellular pseudoranges may be obtained, wherein suchcellular psuedoranges may be used in a cluster analysis technique todisambiguate MS locations identified by the satellite pseudoranges.Moreover, the determination of a location hypothesis is performed, in atleast one embodiment, at a site remote from the target MS 140, such asthe location center/gateway 142, or another site that communicates withthe location center/gateway for supplying a resulting MS location to thegateway. Alternatively, the target MS 140 may perform the calculationsto determine its own location. Note that this alternative technique maybe particularly useful when the target MS 140 is a mobile base station148.

MS Status Repository Embodiment

The MS status repository 1338 is a run-time storage manager for storinglocation hypotheses from previous activations of the location engine 139(as well as the output target MS location estimate(s)) so that a targetMS may be tracked using target MS location hypotheses from previouslocation engine 139 activations to determine, for example, a movement ofthe target MS between evaluations of the target MS location. Thus, byretaining a moving window of previous location hypotheses used inevaluating positions of a target MS, measurements of the target MS'svelocity, acceleration, and likely next position may be determined bythe location hypothesis analyzer 1332. Further, by providingaccessibility to recent MS location hypotheses, these hypotheses may beused to resolve conflicts between hypotheses in a current activation forlocating the target MS; e.g., MS paths may be stored here for use inextrapolating a new location

Mobile Base Station Location Subsystem Description Mobile Base StationSubsystem Introduction

Any collection of mobile electronics (denoted mobile location unit) thatis able to both estimate a location of a target MS 140 and communicatewith the base station network may be utilized by the wireless locationcapabilities disclosed herein to more accurately locate the target MS.Such mobile location units may provide greater target MS locationaccuracy by, for example, homing in on the target MS and by transmittingadditional MS location information to the location center 142. There area number of embodiments for such a mobile location unit contemplated bythe wireless location capabilities disclosed herein. For example, in aminimal version, such the electronics of the mobile location unit may belittle more than an onboard MS 140, a sectored/directional antenna and acontroller for communicating between them. Thus, the onboard MS is usedto communicate with the location center 142 and possibly the target MS140, while the antenna monitors signals for homing in on the target MS140. In an enhanced version of the mobile location unit, a GPS receivermay also be incorporated so that the location of the mobile locationunit may be determined and consequently an estimate of the location ofthe target MS may also be determined. However, such a mobile locationunit is unlikely to be able to determine substantially more than adirection of the target MS 140 via the sectored/directional antennawithout further base station infrastructure cooperation in, for example,determining the transmission power level of the target MS or varyingthis power level. Thus, if the target MS or the mobile location unitleaves the coverage area 120 or resides in a poor communication area, itmay be difficult to accurately determine where the target MS is located.None-the-less, such mobile location units may be sufficient for manysituations, and in fact the wireless location capabilities disclosedherein contemplates their use. However, in cases where directcommunication with the target MS is desired without constant contactwith the base station infrastructure, the wireless location capabilitiesdisclosed herein includes a mobile location unit that is also a scaleddown version of a base station 122. Thus, given that such a mobile basestation or MBS 148 includes at least an onboard MS 140, asectored/directional antenna, a GPS receiver, a scaled down base station122 and sufficient components (including a controller) for integratingthe capabilities of these devices, an enhanced autonomous MS mobilelocation system can be provided that can be effectively used in, forexample, emergency vehicles, air planes and boats. Accordingly, thedescription that follows below describes an embodiment of an MBS 148having the above mentioned components and capabilities for use in avehicle.

As a consequence of the MBS 148 being mobile, there are fundamentaldifferences in the operation of an MBS in comparison to other types ofBS's 122 (152). In particular, other types of base stations have fixedlocations that are precisely determined and known by the locationcenter, whereas a location of an MBS 148 may be known only approximatelyand thus may require repeated and frequent re-estimating. Secondly,other types of base stations have substantially fixed and stablecommunication with the location center (via possibly other BS's in thecase of LBSs 152) and therefore although these BS's may be more reliablein their in their ability to communicate information related to thelocation of a target MS with the location center, accuracy can beproblematic in poor reception areas. Thus, MBSs may be used in areas(such as wilderness areas) where there may be no other means forreliably and cost effectively locating a target MS 140 (i.e., there maybe insufficient fixed location BS's coverage in an area).

FIG. 11 provides a high level block diagram architecture of oneembodiment of the MBS location subsystem 1508. Accordingly, an MBS mayinclude components for communicating with the fixed location BS networkinfrastructure and the location center 142 via an on-board transceiver1512 that is effectively an MS 140 integrated into the locationsubsystem 1508. Thus, if the MBS 148 travels through an area having poorinfrastructure signal coverage, then the MBS may not be able tocommunicate reliably with the location center 142 (e.g., in rural ormountainous areas having reduced wireless telephony coverage). So it isdesirable that the MBS 148 must be capable of functioning substantiallyautonomously from the location center. In one embodiment, this impliesthat each MBS 148 must be capable of estimating both its own location aswell as the location of a target MS 140.

Additionally, many commercial wireless telephony technologies requireall BS's in a network to be very accurately time synchronized both fortransmitting MS voice communication as well as for other services suchas MS location. Accordingly, the MBS 148 will also require such timesynchronization. However, since an MBS 148 may not be in constantcommunication with the fixed location BS network (and indeed may beoff-line for substantial periods of time), on-board highly accuratetiming device may be necessary. In one embodiment, such a device may bea commercially available ribidium oscillator 1520 as shown in FIG. 11.

Since the MBS 148, includes a scaled down version of a BS 122 (denoted1522 in FIG. 11), it is capable of performing most typical BS 122 tasks,albeit on a reduced scale. In particular, the base station portion ofthe MBS 148 can:

-   -   (a) raise/lower its pilot channel signal strength,    -   (b) be in a state of soft hand-off with an MS 140, and/or    -   (c) be the primary BS 122 for an MS 140, and consequently be in        voice communication with the target MS (via the MBS operator        telephony interface 1524) if the MS supports voice        communication.        Further, the MBS 148 can, if it becomes the primary base station        communicating with the MS 140, request the MS to raise/lower its        power or, more generally, control the communication with the MS        (via the base station components 1522). However, since the MBS        148 will likely have substantially reduced telephony traffic        capacity in comparison to a standard infrastructure base station        122, note that the pilot channel for the MBS is preferably a        nonstandard pilot channel in that it should not be identified as        a conventional telephony traffic bearing BS 122 by MS's seeking        normal telephony communication. Thus, a target MS 140 requesting        to be located may, depending on its capabilities, either        automatically configure itself to scan for certain predetermined        MBS pilot channels, or be instructed via the fixed location base        station network (equivalently BS infrastructure) to scan for a        certain predetermined MBS pilot channel.

Moreover, the MBS 148 has an additional advantage in that it cansubstantially increase the reliability of communication with a target MS140 in comparison to the base station infrastructure by being able tomove toward or track the target MS 140 even if this MS is in (or movesinto) a reduced infrastructure base station network coverage area.Furthermore, an MBS 148 may preferably use a directional or smartantenna 1526 to more accurately locate a direction of signals from atarget MS 140. Thus, the sweeping of such a smart antenna 1526(physically or electronically) provides directional informationregarding signals received from the target MS 140. That is, suchdirectional information is determined by the signal propagation delay ofsignals from the target MS 140 to the angular sectors of one of moredirectional antennas 1526 on-board the MBS 148.

Before proceeding to further details of the MBS location subsystem 1508,an example of the operation of an MBS 148 in the context of respondingto a 911 emergency call is given. In particular, this example describesthe high level computational states through which the MBS 148transitions, these states also being illustrated in the state transitiondiagram of FIG. 12. Note that this figure illustrates the primary statetransitions between these MBS 148 states, wherein the solid statetransitions are indicative of a typical “ideal” progression whenlocating or tracking a target MS 140, and the dashed state transitionsare the primary state reversions due, for example, to difficulties inlocating the target MS 140.

Accordingly, initially the MBS 148 may be in an inactive state 1700,wherein the MBS location subsystem 1508 is effectively available forvoice or data communication with the fixed location base stationnetwork, but the MS 140 locating capabilities of the MBS are not active.From the inactive state 1700 the MBS (e.g., a police or rescue vehicle)may enter an active state 1704 once an MBS operator has logged onto theMBS location subsystem of the MBS, such logging being forauthentication, verification and journaling of MBS 148 events. In theactive state 1704, the MBS may be listed by a 911 emergency centerand/or the location center 142 as eligible for service in responding toa 911 request. From this state, the MBS 148 may transition to a readystate 1708 signifying that the MBS is ready for use in locating and/orintercepting a target MS 140. That is, the MBS 148 may transition to theready state 1708 by performing the following steps:

-   -   (1a) Synchronizing the timing of the location subsystem 1508        with that of the base station network infrastructure. In one        embodiment, when requesting such time synchronization from the        base station infrastructure, the MBS 148 will be at a        predetermined or well known location so that the MBS time        synchronization may adjust for a known amount of signal        propagation delay in the synchronization signal.    -   (1b) Establishing the location of the MBS 148. In one        embodiment, this may be accomplished by, for example, an MBS        operator identifying the predetermined or well known location at        which the MBS 148 is located.    -   (1c) Communicating with, for example, the 911 emergency center        via the fixed location base station infrastructure to identify        the MBS 148 as in the ready state.

Thus, while in the ready state 1708, as the MBS 148 moves, it has itslocation repeatedly (re)-estimated via, for example, GPS signals,location center 142S location estimates from the base stations 122 (and152), and an on-board deadreckoning subsystem 1527 having an MBSlocation estimator according to the programs described hereinbelow.However, note that the accuracy of the base station time synchronization(via the ribidium oscillator 1520) and the accuracy of the MBS 148location may need to both be periodically recalibrated according to (1a)and (1b) above.

Assuming a 911 signal is transmitted by a target MS 140, this signal istransmitted, via the fixed location base station infrastructure, to the911 emergency center and the location center 142, and assuming the MBS148 is in the ready state 1708, if a corresponding 911 emergency requestis transmitted to the MBS (via the base station infrastructure) from the911 emergency center or the location center, then the MBS may transitionto a seek state 1712 by performing the following steps:

-   -   (2a) Communicating with, for example, the 911 emergency response        center via the fixed location base station network to receive        the PN code for the target MS to be located (wherein this        communication is performed using the MS-like transceiver 1512        and/or the MBS operator telephony interface 1524).    -   (2b) Obtaining a most recent target MS location estimate from        either the 911 emergency center or the location center 142.    -   (2c) Inputting by the MBS operator an acknowledgment of the        target MS to be located, and transmitting this acknowledgment to        the 911 emergency response center via the transceiver 1512.

Subsequently, when the MBS 148 is in the seek state 1712, the MBS maycommence toward the target MS location estimate provided. Note that itis likely that the MBS is not initially in direct signal contact withthe target MS. Accordingly, in the seek state 1712 the following stepsmay be, for example, performed:

-   -   (3a) The location center 142 or the 911 emergency response        center may inform the target MS, via the fixed location base        station network, to lower its threshold for soft hand-off and at        least periodically boost its location signal strength.        Additionally, the target MS may be informed to scan for the        pilot channel of the MBS 148. (Note the actions here are not,        actions performed by the MBS 148 in the “seek state”; however,        these actions are given here for clarity and completeness.)    -   (3b) Repeatedly, as sufficient new MS location information is        available, the location center 142 provides new MS location        estimates to the MBS 148 via the fixed location base station        network.    -   (3c) The MBS repeatedly provides the MBS operator with new        target MS location estimates provided substantially by the        location center via the fixed location base station network.    -   (3d) The MBS 148 repeatedly attempts to detect a signal from the        target MS using the PN code for the target MS.    -   (3e) The MBS 148 repeatedly estimates its own location (as in        other states as well), and receives MBS location estimates from        the location center.

Assuming that the MBS 148 and target MS 140 detect one another (whichtypically occurs when the two units are within 0.25 to 3 miles of oneanother), the MBS enters a contact state 1716 when the target MS 140enters a soft hand-off state with the MBS. Accordingly, in the contactstate 1716, the following steps are, for example, performed:

-   -   (4a) The MBS 148 repeatedly estimates its own location.    -   (4b) Repeatedly, the location center 142 provides new target MS        140 and MBS location estimates to the MBS 148 via the fixed        location base infrastructure network.    -   (4c) Since the MBS 148 is at least in soft hand-off with the        target MS 140, the MBS can estimate the direction and distance        of the target MS itself using, for example, detected target MS        signal strength and TOA as well as using any recent location        center target MS location estimates.    -   (4d) The MBS 148 repeatedly provides the MBS operator with new        target MS location estimates provided using MS location        estimates provided by the MBS itself and by the location center        via the fixed location base station network.

When the target MS 140 detects that the MBS pilot channel issufficiently strong, the target MS may switch to using the MBS 148 asits primary base station. When this occurs, the MBS enters a controlstate 1720, wherein the following steps are, for example, performed:

-   -   (5a) The MBS 148 repeatedly estimates its own location.    -   (5b) Repeatedly, the location center 142 provides new target MS        and MBS location estimates to the MBS 148 via the network of        base stations 122 (152).    -   (5c) The MBS 148 estimates the direction and distance of the        target MS 140 itself using, for example, detected target MS        signal strength and TOA as well as using any recent location        center target MS location estimates.    -   (5d) The MBS 148 repeatedly provides the MBS operator with new        target MS location estimates provided using MS location        estimates provided by the MBS itself and by the location center        142 via the fixed location base station network.    -   (5e) The MBS 148 becomes the primary base station for the target        MS 140 and therefore controls at least the signal strength        output by the target MS.

Note, there can be more than one MBS 148 tracking or locating an MS 140.There can also be more than one target MS 140 to be tracked concurrentlyand each target MS being tracked may be stationary or moving.

MBS Subsystem Architecture

An MBS 148 uses MS signal characteristic data for locating the MS 140.The MBS 148 may use such signal characteristic data to facilitatedetermining whether a given signal from the MS is a “direct shot” or anmultipath signal. That is, in one embodiment, the MBS 148 attempts todetermine or detect whether an MS signal transmission is receiveddirectly, or whether the transmission has been reflected or deflected.For example, the MBS may determine whether the expected signal strength,and TOA agree in distance estimates for the MS signal transmissions.Note, other signal characteristics may also be used, if there aresufficient electronics and processing available to the MBS 148; i.e.,determining signal phase and/or polarity as other indications ofreceiving a “direct shot” from an MS 140.

In one embodiment, the MBS 148 (FIG. 11) includes an MBS controller 1533for controlling the location capabilities of the MBS 148. In particular,the MBS controller 1533 initiates and controls the MBS state changes asdescribed in FIG. 12. Additionally, the MBS controller 1533 alsocommunicates with the location controller 1535, wherein this lattercontroller controls MBS activities related to MBS location and target MSlocation. The location controller 1535 receives data input from an eventgenerator 1537 for generating event records to be provided to thelocation controller 1535. For example, records may be generated fromdata input received from: (a) the vehicle movement detector 1539indicating that the MBS 148 has moved at least a predetermined amountand/or has changed direction by at least a predetermined angle, or (b)the MBS signal processing subsystem 1541 indicating that the additionalsignal measurement data has been received from either the locationcenter 142 or the target MS 140. Note that the MBS signal processingsubsystem 1541, in one embodiment, is similar to the signal processingsubsystem 1220 of the location center 142. may have multiple commandschedulers. In particular, a scheduler 1528 for commands related tocommunicating with the location center 142, a scheduler 1530 forcommands related to GPS communication (via GPS receiver 1531), ascheduler 1529 for commands related to the frequency and granularity ofthe reporting of MBS changes in direction and/or position via the MBSdead reckoning subsystem 1527 (note that this scheduler is potentiallyoptional and that such commands may be provided directly to thedeadreckoning estimator 1544), and a scheduler 1532 for communicatingwith the target MS(s) 140 being located. Further, it is assumed thatthere is sufficient hardware and/or software to appear to performcommands in different schedulers substantially concurrently.

In order to display an MBS computed location of a target MS 140, alocation of the MBS must be known or determined. Accordingly, each MBS148 has a plurality of MBS location estimators (or hereinafter alsosimply referred to as location estimators) for determining the locationof the MBS. Each such location estimator computes MBS locationinformation such as MBS location estimates, changes to MBS locationestimates, or, an MBS location estimator may be an interface forbuffering and/or translating a previously computed MBS location estimateinto an appropriate format. In particular, the MBS location module 1536,which determines the location of the MBS, may include the following MBSlocation estimators 1540 (also denoted baseline location estimators):

-   -   (a) a GPS location estimator 1540 a (not individually shown) for        computing an MBS location estimate using GPS signals,    -   (b) a location center location estimator 1540 b (not        individually shown) for buffering and/or translating an MBS        estimate received from the location center 142,    -   (c) an MBS operator location estimator 1540 c (not individually        shown) for buffering and/or translating manual MBS location        entries received from an MBS location operator, and    -   (d) in some MBS embodiments, an LBS location estimator 1540 d        (not individually shown) for the activating and deactivating of        LBS's 152. Note that, in high multipath areas and/or stationary        base station marginal coverage areas, such low cost location        base stations 152 (LBS) may be provided whose locations are        fixed and accurately predetermined and whose signals are        substantially only receivable within a relatively small range        (e.g., 2000 feet), the range potentially being variable. Thus,        by communicating with the LBS's 152 directly, the MBS 148 may be        able to quickly use the location information relating to the        location base stations for determining its location by using        signal characteristics obtained from the LBSs 152.        Note that each of the MBS baseline location estimators 1540,        such as those above, provide an actual MBS location rather than,        for example, a change in an MBS location. Further note that it        is an aspect of the wireless location capabilities disclosed        herein that additional MBS baseline location estimators 1540 may        be easily integrated into the MBS location subsystem 1508 as        such baseline location estimators become available. For example,        a baseline location estimator that receives MBS location        estimates from reflective codes provided, for example, on        streets or street signs can be straightforwardly incorporated        into the MBS location subsystem 1508.

Additionally, note that a plurality of MBS location technologies andtheir corresponding MBS location estimators are utilized due to the factthat there is currently no single location technology available that isboth sufficiently fast, accurate and accessible in substantially allterrains to meet the location needs of an MBS 148. For example, in manyterrains GPS technologies may be sufficiently accurate; however, GPStechnologies: (a) may require a relatively long time to provide aninitial location estimate (e.g., greater than 2 minutes); (b) when GPScommunication is disturbed, it may require an equally long time toprovide a new location estimate; (c) clouds, buildings and/or mountainscan prevent location estimates from being obtained; (d) in some casessignal reflections can substantially skew a location estimate. Asanother example, an MBS 148 may be able to use triangulation ortrilateralization technologies to obtain a location estimate; however,this assumes that there is sufficient (fixed location) infrastructure BScoverage in the area the MBS is located. Further, it is well known thatthe multipath phenomenon can substantially distort such locationestimates. Thus, for an MBS 148 to be highly effective in variedterrains, an MBS is provided with a plurality of location technologies,each supplying an MBS location estimate.

In fact, much of the architecture of the location engine 139 could beincorporated into an MBS 148. For example, in some embodiments of theMBS 148, the following FOMs 1224 may have similar location modelsincorporated into the MBS:

-   -   (a) a variation of the TCSO FOM 1224 wherein TOA signals from        communicating fixed location BS's are received (via the MBS        transceiver 1512) by the MBS and used for providing a location        estimate;    -   (b) a variation of the artificial neural net based FOMs 1224 (or        more generally a location learning or a classification model)        may be used to provide MBS location estimates via, for example,        learned associations between fixed location BS signal        characteristics and geographic locations;    -   (c) an LBS location FOM 1224 for providing an MBS with the        ability to activate and deactivate LBS's to provide (positive)        MBS location estimates as well as negative MBS location regions        (i.e., regions where the MBS is unlikely to be since one or more        LBS's are not detected by the MBS transceiver);    -   (d) one or more MBS location reasoning agents and/or a location        estimate heuristic agents for resolving MBS location estimate        conflicts and providing greater MBS location estimate accuracy.        For example, modules similar to the analytical reasoner module        1416 and the historical location reasoner module 1424.

However, for those MBS location models requiring communication with thebase station infrastructure, an alternative embodiment is to rely on thelocation center 142 to perform the computations for at least some ofthese MBS FOM models. That is, since each of the MBS location modelsmentioned immediately above require communication with the network offixed location BS's 122 (152), it may be advantageous to transmit MBSlocation estimating data to the location center 142 as if the MBS wereanother MS 140 for the location center to locate, and thereby rely onthe location estimation capabilities at the location center rather thanduplicate such models in the MBS 148. The advantages of this approachare that:

-   -   (a) an MBS is likely to be able to use less expensive processing        power and software than that of the location center;    -   (b) an MBS is likely to require substantially less memory,        particularly for data bases, than that of the location center.

As will be discussed further below, in one embodiment of the MBS 148,there are confidence values assigned to the locations output by thevarious location estimators 1540. Thus, the confidence for a manualentry of location data by an MBS operator may be rated the highest andfollowed by the confidence for (any) GPS location data, followed by theconfidence for (any) location center location 142 estimates, followed bythe confidence for (any) location estimates using signal characteristicdata from LBSs. However, such prioritization may vary depending on, forinstance, the radio coverage area 120. In an one embodiment of thewireless location capabilities disclosed herein, it is an aspect of thewireless location capabilities disclosed herein that for MBS locationdata received from the GPS and location center, their confidences mayvary according to the area in which the MBS 148 resides. That is, if itis known that for a given area, there is a reasonable probability that aGPS signal may suffer multipath distortions and that the location centerhas in the past provided reliable location estimates, then theconfidences for these two location sources may be reversed.

In one embodiment of the wireless location capabilities disclosedherein, MBS operators may be requested to occasionally manually enterthe location of the MBS 148 when the MBS is stationary for determiningand/or calibrating the accuracy of various MBS location estimators.

There is an additional important source of location information for theMBS 148 that is incorporated into an MBS vehicle (such as a policevehicle) that has no comparable functionality in the network of fixedlocation BS's. That is, the MBS 148 may use deadreckoning informationprovided by a deadreckoning MBS location estimator 1544 whereby the MBSmay obtain MBS deadreckoning location change estimates. Accordingly, thedeadreckoning MBS location estimator 1544 may use, for example, anon-board gyroscope 1550, a wheel rotation measurement device (e.g.,odometer) 1554, and optionally an accelerometer (not shown). Thus, sucha deadreckoning MBS location estimator 1544 periodically provides atleast MBS distance and directional data related to MBS movements from amost recent MBS location estimate. More precisely, in the absence of anyother new MBS location information, the deadreckoning MBS locationestimator 1544 outputs a series of measurements, wherein each suchmeasurement is an estimated change (or delta) in the position of the MBS148 between a request input timestamp and a closest time prior to thetimestamp, wherein a previous deadreckoning terminated. Thus, eachdeadreckoning location change estimate includes the following fields:

-   -   (a) an “earliest timestamp” field for designating the start time        when the deadreckoning location change estimate commences        measuring a change in the location of the MBS;    -   (b) a “latest timestamp” field for designating the end time when        the deadreckoning location change estimate stops measuring a        change in the location of the MBS; and    -   (c) an MBS location change vector.        That is, the “latest timestamp” is the timestamp input with a        request for deadreckoning location data, and the “earliest        timestamp” is the timestamp of the closest time, T, prior to the        latest timestamp, wherein a previous deadreckoning output has        its a timestamp at a time equal to T.

Further, the frequency of such measurements provided by thedeadreckoning subsystem 1527 may be adaptively provided depending on thevelocity of the MBS 148 and/or the elapsed time since the most recentMBS location update. Accordingly, the architecture of at least someembodiments of the MBS location subsystem 1508 must be such that it canutilize such deadreckoning information for estimating the location ofthe MBS 148.

In one embodiment of the MBS location subsystem 1508 described infurther detail hereinbelow, the outputs from the deadreckoning MBSlocation estimator 1544 are used to synchronize MBS location estimatesfrom different MBS baseline location estimators. That is, since such adeadreckoning output may be requested for substantially any time fromthe deadreckoning MBS location estimator, such an output can berequested for substantially the same point in time as the occurrence ofthe signals from which a new MBS baseline location estimate is derived.Accordingly, such a deadreckoning output can be used to update other MBSlocation estimates not using the new MBS baseline location estimate.

It is assumed that the error with dead reckoning increases withdeadreckoning distance. Accordingly, it is an aspect of the embodimentof the MBS location subsystem 1508 that when incrementally updating thelocation of the MBS 148 using deadreckoning and applying deadreckoninglocation change estimates to a “most likely area” in which the MBS 148is believed to be, this area is incrementally enlarged as well asshifted. The enlargement of the area is used to account for theinaccuracy in the deadreckoning capability. Note, however, that thedeadreckoning MBS location estimator is periodically reset so that theerror accumulation in its outputs can be decreased. In particular, suchresetting occurs when there is a high probability that the location ofthe MBS is known. For example, the deadreckoning MBS location estimatormay be reset when an MBS operator manually enters an MBS location orverifies an MBS location, or a computed MBS location has sufficientlyhigh confidence.

Thus, due to the MBS 148 having less accurate location information (bothabout itself and a target MS 140), and further that deadreckoninginformation must be utilized in maintaining MBS location estimates, afirst embodiment of the MBS location subsystem architecture is somewhatdifferent from the location engine 139 architecture. That is, thearchitecture of this first embodiment is simpler than that of thearchitecture of the location engine 139. However, it important to notethat, at a high level, the architecture of the location engine 139 mayalso be applied for providing a second embodiment of the MBS locationsubsystem 1508, as one skilled in the art will appreciate afterreflecting on the architectures and processing provided at an MBS 148.For example, an MBS location subsystem 1508 architecture may be providedthat has one or more first order models 1224 whose output is suppliedto, for example, a blackboard or expert system for resolving MBSlocation estimate conflicts, such an architecture being analogous to oneembodiment of the location engine 139 architecture.

Furthermore, it is also an important aspect of the wireless locationcapabilities disclosed herein that, at a high level, the MBS locationsubsystem architecture may also be applied as an alternativearchitecture for the location engine 139. For example, in one embodimentof the location engine 139, each of the first order models 1224 mayprovide its MS location hypothesis outputs to a corresponding “locationtrack,” analogous to the MBS location tracks described hereinbelow, andsubsequently, a most likely MS current location estimate may bedeveloped in a “current location track” (also described hereinbelow)using the most recent location estimates in other location tracks. Thus,the location estimating models of the location center 139 and those ofthe MBS 148 are may be interchanged depending on the where it is deemedmost appropriate for such each such model to reside. Additionally, notethat in different embodiments of the wireless location capabilitiesdisclosed herein, various combinations of the location center locationarchitecture and the mobile station architecture may be utilized ateither the location center or the MBS 148. Thus, by providingsubstantially all location estimating computational models at thelocation center 142, the models described here for locating the MBS 148(and equivalently, its incorporated MS 140) can be used for locatingother MSs 140 that are be capable of supporting transmission of wirelesssignal measurements that relate to models requiring the additionalelectronics available at the MBS 140 (e.g., GPS or other satellitesignals used for location).

Further, note that the ideas and methods discussed here relating to MBSlocation estimators 1540 and MBS location tracks, and, the relatedprograms hereinbelow are sufficiently general so that these ideas andmethods may be applied in a number of contexts related to determiningthe location of a device capable of movement and wherein the location ofthe device must be maintained in real time. For example, the presentideas and methods may be used by a robot in a very cluttered environment(e.g., a warehouse), wherein the robot has access: (a) to a plurality of“robot location estimators” that may provide the robot with sporadiclocation information, and (b) to a deadreckoning location estimator.

Each MBS 148, additionally, has a location display (denoted the MBSoperator visual user interface 1558 in FIG. 11) where area maps that maybe displayed together with location data. In particular, MS locationdata may be displayed on this display as a nested collection of areas,each smaller nested area being the most likely area within (any)encompassing area for locating a target MS 140. Note that the MBScontroller algorithm below may be adapted to receive location center 142data for displaying the locations of other MBSs 148 as well as targetMSs 140.

Further, the MBS 148 may constrain any location estimates to streets ona street map using the MBS location snap to street module 1562. Forexample, an estimated MBS location not on a street may be “snapped to” anearest street location. Note that a nearest street location determinermay use “normal” orientations of vehicles on streets as a constraint onthe nearest street location. Particularly, if an MBS 148 is moving attypical rates of speed and acceleration, and without abrupt changesdirection. For example, if the deadreckoning MBS location estimator 1544indicates that the MBS 148 is moving in a northerly direction, then thestreet snapped to should be a north-south running street. Moreover, theMBS location snap to street module 1562 may also be used to enhancetarget MS location estimates when, for example, it is known or suspectedthat the target MS 140 is in a vehicle and the vehicle is moving attypical rates of speed. Furthermore, the snap to street location module1562 may also be used in enhancing the location of a target MS 140 byeither the MBS 148 or by the location engine 139. In particular, thelocation estimator 1344 or an additional module between the locationestimator 1344 and the output gateway 1356 may utilize an embodiment ofthe snap to street location module 1562 to enhance the accuracy oftarget MS 140 location estimates that are known to be in vehicles. Notethat this may be especially useful in locating stolen vehicles that haveembedded wireless location transceivers (MSs 140), wherein appropriatewireless signal measurements can be provided to the location center 142.

MBS Data Structure Remarks

Assuming the existence of at least some of the location estimators 1540that were mentioned above, the discussion here refers substantially tothe data structures and their organization as illustrated in FIG. 13.

The location estimates (or hypotheses) for an MBS 148 determining itsown location each have an error or range estimate associated with theMBS location estimate. That is, each such MBS location estimate includesa “most likely MBS point location” within a “most likely area”. The“most likely MBS point location” is assumed herein to be the centroid ofthe “most likely area.” In one embodiment of the MBS location subsystem1508, a nested series of “most likely areas” may be provided about amost likely MBS point location. However, to simplify the discussionherein each MBS location estimate is assumed to have a single “mostlikely area”. One skilled in the art will understand how to provide suchnested “most likely areas” from the description herein. Additionally, itis assumed that such “most likely areas” are not grossly oblong; i.e.,area cross sectioning lines through the centroid of the area do not havelarge differences in their lengths. For example, for any such “mostlikely area”, A, no two such cross sectioning lines of A through thecentroid thereof may have lengths that vary by more than a factor offive.

Each MBS location estimate also has a confidence associated therewithproviding a measurement of the perceived accuracy of the MBS being inthe “most likely area” of the location estimate.

A (MBS) “location track” is an data structure (or object) having a queueof a predetermined length for maintaining a temporal (timestamp)ordering of “location track entries” such as the location track entries1770 a, 1770 b, 1774 a, 1774 b, 1778 a, 1778 b, 1782 a, 1782 b, and 1786a (FIG. 13), wherein each such MBS location track entry is an estimateof the location of the MBS at a particular corresponding time.

There is an MBS location track for storing MBS location entries obtainedfrom MBS location estimation information from each of the MBS baselinelocation estimators described above (i.e., a GPS location track 1750 forstoring MBS location estimations obtained from the GPS locationestimator 1540, a location center location track 1754 for storing MBSlocation estimations obtained from the location estimator 1540 derivingits MBS location estimates from the location center 142, an LBS locationtrack 1758 for storing MBS location estimations obtained from thelocation estimator 1540 deriving its MBS location estimates from basestations 122 and/or 152, and a manual location track 1762 for MBSoperator entered MBS locations). Additionally, there is one furtherlocation track, denoted the “current location track” 1766 whose locationtrack entries may be derived from the entries in the other locationtracks (described further hereinbelow). Further, for each locationtrack, there is a location track head that is the head of the queue forthe location track. The location track head is the most recent (andpresumably the most accurate) MBS location estimate residing in thelocation track. Thus, for the GPS location track 1750 has location trackhead 1770; the location center location track 1754 has location trackhead 1774; the LBS location track 1758 has location track head 1778; themanual location track 1762 has location track head 1782; and the currentlocation track 1766 has location track head 1786. Additionally, fornotational convenience, for each location track, the time series ofprevious MBS location estimations (i.e., location track entries) in thelocation track will herein be denoted the “path for the location track.”Such paths are typically the length of the location track queuecontaining the path. Note that the length of each such queue may bedetermined using at least the following considerations:

-   -   (i) In certain circumstances (described hereinbelow), the        location track entries are removed from the head of the location        track queues so that location adjustments may be made. In such a        case, it may be advantageous for the length of such queues to be        greater than the number of entries that are expected to be        removed;    -   (ii) In determining an MBS location estimate, it may be        desirable in some embodiments to provide new location estimates        based on paths associated with previous MBS location estimates        provided in the corresponding location track queue.        Also note that it is within the scope of the wireless location        capabilities disclosed herein that the location track queue        lengths may be a length of one.

Regarding location track entries, each location track entry includes:

-   -   (a) a “derived location estimate” for the MBS that is derived        using at least one of:        -   (i) at least a most recent previous output from an MBS            baseline location estimator 1540 (i.e., the output being an            MBS location estimate);        -   (ii) deadreckoning output information from the deadreckoning            subsystem 1527.    -   Further note that each output from an MBS location estimator has        a “type” field that is used for identifying the MBS location        estimator of the output.    -   (b) an “earliest timestamp” providing the time/date when the        earliest MBS location information upon which the derived        location estimate for the MBS depends. Note this will typically        be the timestamp of the earliest MBS location estimate (from an        MBS baseline location estimator) that supplied MBS location        information used in deriving the derived location estimate for        the MBS 148.    -   (c) a “latest timestamp” providing the time/date when the latest        MBS location information upon which the derived location        estimate for the MBS depends. Note that earliest        timestamp=latest timestamp only for so called “baseline entries”        as defined hereinbelow. Further note that this attribute is the        one used for maintaining the “temporal (timestamp) ordering” of        location track entries.    -   (d) A “deadreckoning distance” indicating the total distance        (e.g., wheel turns or odometer difference) since the most        recently previous baseline entry for the corresponding MBS        location estimator for the location track to which the location        track entry is assigned.

For each MBS location track, there are two categories of MBS locationtrack entries that may be inserted into a MBS location track:

-   -   (a) “baseline” entries, wherein each such baseline entry        includes (depending on the location track) a location estimate        for the MBS 148 derived from: (i) a most recent previous output        either from a corresponding MBS baseline location estimator,        or (ii) from the baseline entries of other location tracks (this        latter case being the for the “current” location track);    -   (b) “extrapolation” entries, wherein each such entry includes an        MBS location estimate that has been extrapolated from the (most        recent) location track head for the location track (i.e., based        on the track head whose “latest timestamp” immediately precedes        the latest timestamp of the extrapolation entry). Each such        extrapolation entry is computed by using data from a related        deadreckoning location change estimate output from the        deadreckoning MBS location estimator 1544. Each such        deadreckoning location change estimate includes measurements        related to changes or deltas in the location of the MBS 148.        More precisely, for each location track, each extrapolation        entry is determined using: (i) a baseline entry, and (ii) a set        of one or more (i.e., all later occurring) deadreckoning        location change estimates in increasing “latest timestamp”        order. Note that for notational convenience this set of one or        more deadreckoning location change estimates will be denoted the        “deadreckoning location change estimate set” associated with the        extrapolation entry resulting from this set.    -   (c) Note that for each location track head, it is either a        baseline entry or an extrapolation entry. Further, for each        extrapolation entry, there is a most recent baseline entry, B,        that is earlier than the extrapolation entry and it is this B        from which the extrapolation entry was extrapolated. This        earlier baseline entry, B, is hereinafter denoted the “baseline        entry associated with the extrapolation entry.” More generally,        for each location track entry, T, there is a most recent        previous baseline entry, B, associated with T, wherein if T is        an extrapolation entry, then B is as defined above, else if T is        a baseline entry itself, then T=B. Accordingly, note that for        each extrapolation entry that is the head of a location track,        there is a most recent baseline entry associated with the        extrapolation entry.        Further, there are two categories of location tracks:    -   (a) “baseline location tracks,” each having baseline entries        exclusively from a single predetermined MBS baseline location        estimator; and    -   (b) a “current” MBS location track having entries that are        computed or determined as “most likely” MBS location estimates        from entries in the other MBS location tracks.

MBS Location Estimating Strategy

In order to be able to properly compare the track heads to determine themost likely MBS location estimate it is an aspect of the wirelesslocation capabilities disclosed herein that the track heads of alllocation tracks include MBS location estimates that are forsubstantially the same (latest) timestamp. However, the MBS locationinformation from each MBS baseline location estimator is inherentlysubstantially unpredictable and unsynchronized. In fact, the only MBSlocation information that may be considered predicable and controllableis the deadreckoning location change estimates from the deadreckoningMBS location estimator 1544 in that these estimates may reliably beobtained whenever there is a query from the location controller 1535 forthe most recent estimate in the change of the location for the MBS 148.Consequently (referring to FIG. 13), synchronization records 1790(having at least a 1790 b portion, and in some cases also having a 1790a portion) may be provided for updating each location track with a newMBS location estimate as a new track head. In particular, eachsynchronization record includes a deadreckoning location change estimateto be used in updating all but at most one of the location track headswith a new MBS location estimate by using a deadreckoning locationchange estimate in conjunction with each MBS location estimate from anMBS baseline location estimator, the location track heads may besynchronized according to timestamp. More precisely, for each MBSlocation estimate, E, from an MBS baseline location estimator, thewireless location capabilities disclosed herein also substantiallysimultaneously queries the deadreckoning MBS location estimator for acorresponding most recent change in the location of the MBS 148.Accordingly, E and the retrieved MBS deadreckoning location changeestimate, C, have substantially the same “latest timestamp”. Thus, thelocation estimate E may be used to create a new baseline track head forthe location track having the corresponding type for E, and C may beused to create a corresponding extrapolation entry as the head of eachof the other location tracks. Accordingly, since for each MBS locationestimate, E, there is a MBS deadreckoning location change estimate, C,having substantially the same “latest timestamp”, E and C will behereinafter referred as “paired.”

High Level Description of a Wireless Platform

FIG. 20 is a high level block diagram illustrating the wirelessapplication platform 2004 of the present disclosure in combination withvarious services and network components with which the platformcommunicates. In particular, the embodiment of FIG. 20 is illustrativeof how the platform 2004 communicates with, e.g., the subscribers (e.g.,users 2008), applications (e.g., applications 2016, 2020, 2024, 2028,and 2032 which may or may not receive wireless location relatedinformation from the wireless location gateway 142), and networkaccessible components (e.g., wireless equipment) for a single commercialwireless carrier. The platform 2004 communicates with subscribers orusers 2008 of the wireless carrier via, e.g., a mobile station 140 incommunication with various provisioning equipment and communicationservices of the wireless carrier, collectively this equipment andcommunication services are identified as carrier network provisioning2012, and may include e.g.:

-   -   1. wireless voice and/or wireless data (local and/or long        distance) services;    -   2. Internet access;    -   3. high speed data and/or Internet services such as (3G, cable,        DSL, ISDN, satellite communications, etc.);    -   4. telephony specific services (e.g., call forwarding, call back        busy, Caller ID, Do Not Disturb, prepaid calling card services,        etc.);    -   5. PBX and/or business network installation and maintenance        services;    -   6. teleconferencing provisioning and services; and/or    -   7. short messaging services (SMS).        More particularly, users 2008 can communicate various requests        to the platform 2004 for various wireless location related        services such as:    -   PR 1. Requests for routing the user from his/her location to a        desired location;    -   PR 2. Requests for information about products, services, places        and/or persons that are geographically related to a location of        the user 2008;    -   PR 3. Requests for displaying and/or modifying, e.g., user        profile information to thereby change access permissions, and/or        profile visibility;    -   PR 4. Requests for activating or deactivating services, e.g.,        wireless services such as hotel concierge wireless location and        routing services offered by hotel, such services capable of,        e.g., being attached and detached from a user's profile as a        unit;    -   PR 5. Requests for procuring products and/or services (location        related or otherwise); and/or    -   PR 6. Standard telephony, Internet and data services.

It is worth noting that embodiments of related wireless platforms havebeen described in the art. In particular, International PatentApplication PCT/US01/02526, filed Jan. 26, 2001 by McDowell et. al.titled: “Method and Apparatus For Sharing Mobile User Event InformationBetween Wireless Between Wireless and Fixed IP Networks” incorporatedherein fully by reference, and, International Patent ApplicationPCT/US02/04533, filed Feb. 15, 2002 by McDowell et. al. titled: “Use OfPresence And Location Information Concerning Wireless Subscribers ForInstant Messaging And Mobile Commerce” also incorporated herein fully byreference. However, these platforms appear directed to short messagingservice applications and ecommerce (i.e., merchant advertising), and donot appear to address issues related to the easy incorporation ofentirely new complex network services, and in particular, for networkservices wherein there is a uniform architecture for communicationsbetween the platform and new network service applications. Instead, thePCT/US02/04533 application is directed to: “the integration of presencedetermination, location determination, Instant Messaging, and mobilecommerce into a functionally seamless system” wherein such presencedetermination “determines whether a mobile device is ON or OFF inreal-time.” So that this system (i.e., McDowell's) “may then share therevenue generated through the sale of subscriber information with theparticipating wireless carriers that host the subscribers.”, and“determines both Internet presence and wireless network presence, andmakes this information available to entities on both networks.” However,the above-identified McDowell et. al. PCT patent applications do provideappropriate supportive and enabling information for the presentdisclosure, and in particular, the platform 2004.

FIG. 22 shows an embodiment of the high level steps performed that canbe performed by the platform 2004. Descriptions of these steps follows:

-   Step 2204: The subscriber interfaces 2104 (FIG. 21) receives a    service request from a user 2008, via the carrier network    provisioning 2012 (FIG. 20). Note that such service requests may be    from users 2008 where such users include not only persons, but also    entities such as businesses, employers, other telecommunication    carriers, government agencies (e.g., command, control, and    communications centers), law enforcement, etc. In at least some    circumstances, the actual payload of the data describing the service    request and/or related data in the request may be encrypted. Thus,    the present step determines whether one or more portions of the    service request is encrypted, and if so, activates the encryption    and decryption component 2108 (FIG. 21) for decrypting the service    request. Encryption/decryption cyphers are well known in the art,    and accordingly will not be discussed at length here. However, the    encryption and decryption component 2108 may support a substantial    number encryption/decryption cyphers. (e.g., RC4 and RSA, by    Security Inc, Belford, Mass., USA) as well as such general    encryption techniques as public/private key cryptographic technique    such as Diffie-Hellman.

Note that the present step may identify, e.g., at least some of thefollowing data items:

-   -   (i) the identity of the requestor;    -   (ii) the identity of an entity (or entities) to whom an action        of the request is directed, e.g., (a) the identity of the person        or MS 140 whose wireless location is requested (this may be the        mobile identification number (MIN) as one skilled in the art        will understand), or (b) the identity of a package whose        whereabouts is being tracked, (c) the location of an MS 140        which to be identified (e.g., in a battlefield context to        determine if the location of the MS corresponds to friend or        foe);    -   (iii) any additional data that may be needed by an application        activated to fulfill the request, e.g., for an MS 140 location        request, this may include the last known location of the MS;    -   (iv) any timing constraints that the service requesting        application should aware of;    -   (v) any authorization code needed for granting access to any        generated information about the entity (e.g., for determining a        subscriber's location, a code indicating that permission has        been obtained to locate the subscriber, or a code indicating        that location of the subscriber is at the request of the        government agency responsible for national security or crime        prevention);    -   (vi) any encryption parameters needed for a resulting response        to the request;    -   (vii) the identity of any specific application to be activated        to fulfill the request;    -   (viii) any billing code required in order to bill for fulfilling        the service request;    -   (ix) a priority for fulfilling the service request (note,        emergency 911 and other time critical life threatening or        emergency services will have highest priority and may pre-empt        other service requests being processed by the platform 2004);    -   (x) identity of all destinations, entities and/or persons to        which the results from the fulfillment (and/or activation) of        the service request is to be transmitted;    -   (xi) any authorization code or protocol to be used in        identifying the appropriate person or entity prior to presenting        information related to the results of the service request.        -   Further note, however, that it is not intended that the user            2008 be required to enter all of the items identified in            this step. In particular, many of these items may be            automatically filled in with default values residing on the            user's service requesting device.

-   Step 2208: With any decryption completed, the service request is now    readable and accordingly may be logged in the user request &    response log management database 2112 (FIG. 21) so that, e.g., (i)    audits can be performed for verifying what service requests have    been received, (ii) analyzing platform 2004 performance, diagnosing    errors in service request processing, and/or statistical analysis of    service request volume may be performed, and (iii) tracking or    identifying criminal behavior and/or misuse of a service offered by    the platform 2004.    -   Regarding the request & response log management database 2112,        this database may capture and store at least most of the        following information related to a service request received by        the platform 2004:        -   (a) The identity of the party initiating the service            request, e.g., a user ID or log in name;        -   (b) The time of receipt of the service request;        -   (c) The identity of the service requested;        -   (d) The priority of the service request (if any provided);        -   (e) Any time constraints that the service request is            imposing (e.g., a response within 30 seconds);        -   (f) Information related to the source of the request, e.g.,            the MIN (or other identification) of an MS 140 requesting            service, or an Internet address of a service requestor;        -   (g) Any authorization code for permitting the service            request to be performed; and        -   (h) Any billing code identifying who is to be charged.

-   Step 2212: Subsequently, a readable version of the service request    is provided to the subscriber identification & application    authorization subsystem 2116 (FIG. 21), wherein the identification    of both the requestor and the application to be activated to fulfill    the service request is determined. The subsystem 2116 may access    various user identification repositories, such as user profile    repositories collectively labeled 2120 (FIG. 21), including customer    care data management systems that are maintained by, e.g., a    wireless carrier responsible for the operation of the platform 2004,    such repositories being, e.g., home location registers (HLRs) and    Visitor Location Registers (VLRs). Additionally, some of the    repositories 2120 may be accessed only via another network carrier    not affiliated or responsible for the operation of the platform    2004. Such repositories may be accessed for obtaining, e.g., (i)    additional user information that may not have been provided with the    service request, and/or (ii) an identification of the carrier    network (if any) to which the user is a subscriber. In particular,    such additional information may relate to an authorization to    activate, e.g., a wireless location based application, and receive a    response therefrom. Note that such authorization may include two    processes: a determination of whether the user is eligible to make    the request (e.g., such eligibility may be substantially determined    according to, e.g., the service package to which the user 2008 has    subscribed and whether the user's subscription remains active), and    a determination as to whether the current service request can be    honored given privacy, security, and/or legal constraints that must    satisfied for fulfilling the service request, e.g., location based    network services where a person different from the user 2008 is to    be located.    -   In one embodiment, if the user 2004 is a roamer (civilian or        military), the network carrier operably responsible for the        platform 2004 may initiate, via the subsystem 2116, a request        for user profile information to be transmitted from the user's        subscriber network or other central profile repository. Various        embodiments of such profiles and/or data within them are        provided throughout this description. Thus, a user profile may        include substantially any user information that is required to        allow or prohibit access, activation, or fulfillment of a        network service by the user, or, by another user where the        requested service, by the other user, requires accessing        information about the user that is identified as being        confidential or private. However, in one preferred embodiment        such user profiles may be automatically requested when the        roamer activates his/her MS 140 for out of network service.        Moreover, it may be the case that when fulfillment of the        service request requires the location or other personal        information (e.g., financial information) of another user or        entity, at least a portion of the profile for this other user or        entity must be queried or accessed for determining whether such        a location activity is permissible and/or legal, and such        information may be substantially only accessible from the        carrier network to which the user is a subscriber.    -   In order to identify the service being requested, the subsystem        2116 can access the user assessable & authorized services        database 2124 (FIG. 21) for determining the services that are        currently accessible from via the platform 2004, e.g., as called        services or platform aware connection services as described in        the Summary section hereinabove. Additionally, the database 2124        may be accessed by the subsystem 2116 for retrieving information        related to who is authorized to access certain services. For        example, certain network services may be available for only a        particular time period(s). For example, a particular network        based game may extend for a predetermined time period such as        three weeks, or may be only played on non-holiday weekends when        there is less network traffic. In such a case, it may more        expedient to associate game activation authorization data with        information identifying the game in the database 2124 than        iteratively modifying, e.g., user 2008 profiles of game players        for indicating when the game can be accessed as a network        service. Additionally, note that a network service that is        malfunctioning may be easily prevented from being accessed if        such authorizations are associated with network service        identifications. Furthermore, it may be the case, that an        alternative service provider may be utilized for fulfilling the        service. Thus, the preferred (now malfunctioning) service        provider may be effectively disconnected from being accessed by        users 2008, and a second less preferred backup network service        activated for the providing substantially the same service in a        manner that is transparent to the users 2008. Examples where        such backup service providers may be desirable are: (i) when        wireless location requests must be fulfilled (e.g., E911        requests) and the primary wireless location service provider is        experiencing operational difficulties, then a second less        desirable backup wireless location service provider may be        easily activated (assuming all communication and data flow paths        with the second location service provider have been previously        established) by merely changing the value of the activation        information for each of the primary and secondary wireless        location service providers in the database 2124, (ii) when a        service provider for an Internet service 2128 (FIG. 21) such as        a service provider for an Internet connection, or some other        Internet accessible service such as a search engine or a        battlefield command and control Internet site becomes        inoperative, then users 2004 may be transparently (or        substantially so) switched to a corresponding backup service        provider for the Internet service. Thus, the database 2124 may        allow for providing a simple and effective technique for        providing the platform 2004 with a measure of fail safeness to        network services that are accessible via the platform 2004.    -   Note that the services & applications 2016 (FIG. 20) are        representative examples of some of the services that may be        requested as called services. However, these services may also        be connection services, e.g., a 911 call may be a voice over IP        connection which also provides the FCC mandated information to        the 911 center. The services identified in 2016 will how be        briefly described:    -   i. Yellow page services related to the purchase of products        and/or services, and in particular electronic networked yellow        page services as described more fully under the section Wireless        Location Applications hereinbelow;    -   ii. Emergency services such as E 911 in the USA (note that        emergency services are typically routed through substantially        dedicated channels; however, it is believed that with increasing        network bandwidth and robustness, such dedicated channels can be        substantially dispensed with and, instead, such emergency        services can be appropriately and timely performed by using the        platform 2004 of the present disclosure. Moreover, by utilizing        the platform 2004, emergency services may be significantly        enhanced by, e.g., accessing the emergency caller's profile and        thereby alerting friends, relatives, neighbors, and/or        appropriate passersby. Additionally, caller medical information        may be provided in the caller's profile such as type of medical        insurance, caller medical conditions, and/or medical personal to        be alerted;    -   iii. 411 information services, and in particular, location based        information services, and more particularly “intelligent”        location based information services such as the location based        routing services described hereinbelow in the section titled        Routing Applications, and the section titled Point of Interest        Applications hereinbelow;    -   iv. Roaming services such as wireless concierge services that        may offered to travelers by, e.g., hotels as described more        fully in the section titled Roaming Services hereinbelow.        -   Note, however, that for different application domains very            different network services may be available. For example, in            a military or battlefield context there may be analogous            services to some of the items (i) through (iv) immediately            above; however, certainly additional network services are            likely such as network services for real time control over            robotic or surveillance battlefield devices.

-   Step 2216: Subsequently, a determination is made by the subscriber    identification & application authorization subsystem 2116 as to    whether the network service request is an emergency such as an E911    request.

-   Step 2220: If the results from Step 2216 is positive, then the    subsystem 2116 activates an emergency protocol for communicating    with one or more emergency response service providers 2132    (represented in FIG. 21 by the 911 processing block 2132), whereby,    e.g., a predetermined series of emergency tasks or steps are    performed for: (i) locating the emergency, (ii) identifying the type    of emergency, and (iii) directing assistance to the emergency or    directing persons out of the emergency. When the platform 2004 is    used for accessing network services within a U.S. commercial mobile    radio provider network (CMRS), the U.S. Federal Communications    Commission (FCC) provides guidelines and mandates regarding how and    what emergency tasks are performed. Such emergency protocols are    well known in the art and are not elaborated on here. However, note    that such emergency protocols may be different when the platform    2004 is utilized in a military or battlefield context, or in the    context of a major disaster such as damage from a hurricane or a    biological terrorist attack in that there may be many requests for    emergency services within a relatively short timeframe (e.g., 1    minute to 12 hours or longer). However, whether the platform 2004 is    utilized in a civilian or military context, a high rate of emergency    service requests can be problematic for the communications network    to appropriately handle. In one embodiment, of the platform 2004,    the subsystem 2116 detects high rates of emergency requests, and    alerts a platform controller 2136 (FIG. 21) which, e.g., allocates    computational resources within the platform 2004, and handles error    or exceptional event processing. The controller 2136 may in one    embodiment, modify the database 2124 so that when the subsystem 2116    subsequently accesses this database for determining an emergency    response service provider to service emergency requests, the    database 2124 commences to distribute the output identifications of    emergency response service over a plurality of such service    providers. Thus, two successive requests for an emergency response    service provider by the subsystem 2116 may result in different in    identifications of two different service providers, whereas without    the controller 2136 database modification, the same emergency    response service provider would have been provided to the subsystem    2116. Note that the database 2124 may use a static or fixed    allocation scheme for allocating emergency service requests among a    plurality of emergency response service providers 2132 operatively    connected to the platform 2004. Alternatively, a dynamic scheme may    be used wherein there is feedback to the platform 2004 (and more    particularly, the controller 2136) from each (or at least some) of    the emergency response service providers 2132 providing data    indicative of the emergency processing loads they are experiencing.    For example, such feedback from an emergency response service    provider may include one or more of: (i) a measurement related to    the number of emergency requests that are queued and not currently    being processed (e.g., the current number or the average over some    time period); (ii) a measurement related to the rate at which    emergency requests are being processed (e.g., an average number of    emergency requests fully processed in a particular time    period); (iii) one or more measurements related to the time to    process a specified number of emergency requests (e.g., an average    time for fully processing a moving window of 10 emergency requests,    a percentage of the number of emergency requests being currently    processed that are identified as likely to require very lengthy or    an indeterminate amount of time to process; (iv) a measurement    related to the overall emergency response processing load (e.g.,    this measurement identified as high whenever a measurement for (i)    above exceeds a predetermined threshold, or a measurement for (iii)    above exceeds a predetermine threshold).    -   Thus, upon receiving such feedback, the controller 2136 may be        able to adjust the distribution of emergency requests among the        emergency response service providers to thereby balance the        loads on these service providers, or provide a higher emergency        response completion rate, or provide a lower average time for        providing an initial response to emergency requests.        Additionally, the controller 2136 may provide instructions to,        e.g., subscriber identification & application authorization        subsystem 2116 so that during such load balancing, geographic        location information of the user initiating emergency or 911        requests is used in the routing of such requests to particular        emergency service providers (e.g., public safety answering        points, or PSAPs). For example, a large hurricane may impact an        area having a radius of 100 miles or more. Accordingly, numerous        emergency service providers local to such an area may be        overwhelmed with emergency calls. Accordingly, one or more        emergency command centers may be setup to coordinate emergency        response services, wherein such emergency command centers        communicate with the emergency service providers (e.g., PSAPs)        in the emergency effected area. Accordingly, when load balancing        is initiated to direct some (or all) calls to alternative        emergency service providers (e.g., PSAPs) instead of such local        emergency service providers, at least emergency command center        communication information is also provided to the alternative        emergency service providers so that they can communicate with        the one or more emergency command centers for the geographic        areas from which such alternative emergency service providers        are receiving emergency requests. Thus, in one embodiment, when        load balancing between emergency service providers (e.g.,        PSAPs), the geographic location of each emergency request may be        determined and used for determining the alternative emergency        service provider to route the request. In particular, the        alternative emergency service provider should have        communications established with the corresponding emergency        command center responsible for the area from which the emergency        request is received. Accordingly, such load balancing may        additionally cause all calls which are to be re-routed from an        overloaded (or non-functioning) emergency service provider to        re-routed one or more predetermined or pre-selected alternative        emergency service providers. Thus, the following substeps may be        performed during load balancing for each emergency request        within an emergency or disaster area: i.e., if at least one load        balancing metric indicates load balancing between an emergency        service provider P and some alternative emergency service        provider Q, is needed, then:        -   Determine a percentage (or other measurement) of the            emergency requests to be off-loaded from P to some Q. In one            embodiment, such a percentage may be: The maximum, less than            or equal to 100 (100 otherwise), of:            -   [100*((terminated requests not processed by P within                time period T)/(emergency requests received by P within                T))+predetermined additional percentage (e.g., 5)], and            -   [100*(1+((emergency requests fulfilled by P within                T)/(emergency requests received by P within T))],        -   wherein the time period T may be, e.g., from one minute to 5            minutes, and wherein T may vary inversely with the number            (or change in number) of emergency call requests in the            immediately preceding one or more time periods (denoted here            the “call volume”). Thus, assuming a substantially inversely            linear relationship between T and the emergency call volume,            if the call volume rises from an average of 50 calls for the            time period sT of a preceding collection of one or more time            periods (e.g., having an average length of 3 minutes) to 100            calls in the current time period T_(C) (e.g., of say 3.5            minutes), then the next time period T_(N) may be between            1.75 and 1.5 minutes depending the number of preceding time            periods used.        -   For each emergency request to be re-routed to an alternative            emergency service provider Q_(i), select Q_(i) according to            whether Q_(i) is configured to communicate with the command            center C for the area containing the geographic location of            the source of the request, and wherein Q_(i) is the first            such configured alternative emergency service provider on a            list of alternative emergency service providers for P that            is not also requiring load balancing.        -   If no Q_(i), was selected in (b) above, notify emergency            command center C.    -   Additionally, such re-routing of emergency requests may also be        dependent upon a geographical location of the emergency caller.        In particular, emergency requests from predetermined        geographical subareas of a overloaded emergency service provider        may be routed to the same alternative emergency service        provider. Note, that such re-routing based on emergency caller        location can be performed by identifying (for wireless emergency        requests) the primary base station with which the caller is in        contact. Accordingly, it is believed that in most emergency or        disaster designated areas, emergency calls from subareas thereof        will be processed by at most one or two emergency service        providers (e.g., PSAPs) while at the same time balancing call        loads between emergency service providers.    -   Moreover, the present step also includes providing what is known        as “reverse 911” protocols, wherein persons in a given area are        alerted to an eminent or likely emergency situation or event        which may be dangerous to them, e.g., an impending flood, an        enemy aircraft that is nearby, a change in the direction of a        forest fire or hurricane, etc. Thus, for such reverse 911        service requests, the requestor is likely to be a governmental        agency or designated agent (e.g., a field observer), and        location information, e.g., indicating the area to likely be        affected by the imminent threat is provided with the service        request. Accordingly, subscribers (and others that can be        contacted) whose locations are identified as being in a        designated area are notified of the danger. Thus, it is an        aspect of the platform 2004 to push certain types of information        to users' MSs 140 such as reverse 911 information.

-   Step 2224: If the result from step 2216 indicates that the service    request is not for an emergency, then in step 2224 the subsystem    2116 may access a home location register for the user, a visitor    location register providing user information, wherein such an access    is for obtaining profile data for the user related to the current    request. That is, the present step accesses the database(s) 2120 for    retrieving profile information for the user 2008 requesting the    service, and/or the user profile information related to the service    or application being requested.

-   Step 2228: In the present step a determination is made by the    subsystem 2116 as to whether the application being requested (or a    comparable application) is known to the platform 2004; e.g.,    registered with the platform so that platform can enable the service    and/or perform accounting for the service. Note that for roaming MS    140 users, they may request one or more services that are not    available in a network in which they are roaming. However,    substantially or somewhat comparable services may be available, and    the platform 2004 may inform such a (roaming) user of the comparable    service for thereby obtaining user input regarding whether to    allocate resources for the comparable service, or alternatively    automatically activate the comparable service for the user. For    example, for a user whose medical condition is monitored    continuously or periodically via automatic transmissions from the    user's MS 140 to a medical monitoring service, the user may roam to    a geographical area where the user's medical monitoring service is    not provided. For instance, a user may have his/her heart rhythms    monitored by a medical monitoring service. However, upon roaming to    an area not covered by the medical monitoring service (or not    covered efficiently due to time delays and/or cost), the user may    be: (i) informed of such lack of coverage, and (ii) allow the user    to request activation of an alternative service, (if available)    and/or the user may automatically be provided with the alternative    service such as a service that merely monitors blood pressure. Other    examples may be also instructive. A user may have contracted with a    particular rental car agency to supply the user with a particular    type of car substantially wherever the user travels, and the user    has requested such a car for his/her arrival in Santa Fe, N. Mex.    However, upon arriving in Santa Fe, N. Mex., the user may be    notified via the platform 2004: (i) that the particular type of car    is unavailable, and (ii) of what alternative car selections the    rental agency has, and/or that other car rental agencies have the    particular car that the user can rent. In another example, a user    may be provided with periodic information regarding another user's    or object's status, e.g., user/object's geographic location, the    temperature of the user/object, a movement of the user/object, a    configuration of user/object (e.g., computer network configuration),    etc. However, if the user/object moves to an area that can not    support (or cost effectively) can support the transmission of such    information, a comparable service (if available) may be offered to    the user.

-   Step 2232: If the result from step 2228 is negative, then in one    embodiment of the present step, an applications controller 2144    (FIG. 21) and more particularly, application access initialization    2148 attempts to obtain data for initializing access to the    requested (or comparable) service, and/or to provide the billing    system 2140 with sufficient information for billing for the service    request. For example, the platform 2004 may request activation    schema or script data from the requested service for activating the    service for the user. Such schema or script data may include    identifications of network bandwidth required/desired, when to    activate the service, the length of time network resources will be    needed, network quality of transmission characteristics    required/desired, and/or payment information for billing the user    via the user's network provider. If the application access    initialization 2148 is successful in obtaining sufficient    information, then the retrieved application request description data    may be in the application requirements database management system    2152. However, in another alternative embodiment of the present    step, the application access initialization 2148 outputs a failure    code for the request, and this code is provided to the subscriber    interfaces component 2104, wherein an appropriate representation of    this failure is presented to the user 2008 by accessing the    presentation engine 2156 for generating a presentation that is    presentable at the user's network device such as an MS 140.    Subsequently, in this alternative embodiment, the process of FIG. 22    terminates relative to the service request being processed.

-   Step 2236: If the result from step 2228 is positive or the requested    application can be otherwise initiated via step 2232, then in one    embodiment the subsystem 2116 determines whether there is    authorization for activating an application for fulfilling the    service request. In one embodiment, the billing system 2140    (FIG. 21) may be accessed for determining whether the request by a    user 2008 should be honored. Note such access to the billing system    2140 may be desirable since an important aspect of the platform 2004    is the ability to provide common network services (and in particular    complex network services, and more particularly, wireless location    based network services) to a large and potentially varying number of    network services. For example, it may be the case that a user 2008    is denied further access to a particular network service by the    platform 2004 due to a delinquent payment or disputed charges, but    the user is given access to other network services (e.g., network    services paid by another, such as an employer, a parent, a financial    institution, etc.).

-   Step 2240: If the result of step 2236 is negative, then in a similar    manner to the alternative embodiment of step 2232 a failure    indication is output to the user.

-   Step 2244: If the result of step 2236 is positive, then the    applications controller 2144 performs the following steps: (a) it    parses the service request for identifying service request specific    data; (b) it prioritizes the service request according to, e.g.,    desired performance requirements (e.g., network bandwidth    requirements, security requirements, encryption requirements,    response requirements, etc.) for fulfilling the service request and    priority; and (c) if needed, determines network access paths for    accessing the application that can fulfill the service request,    and/or activates the request provisioning system 2160 for    determining/allocating network resources such as equipment and    bandwidth (e.g., virtual private communication channels or    allocating bandwidth for a user requested movie to be streamed to    his/her MS 140).

-   Step 2248: In the present step, the applications controller 2144 in    combination with the request provisioning system 2160: (a) accesses    the applications requirements data management system 2152 to    determine what activations of other network services are required by    the current service request being processed by the applications    controller 2144, and (b) determines how such additional network    service output(s) is to be provided to the current service request    being processed; e.g., output format, output timing restrictions,    accuracy restrictions, etc. Note that the applications requirements    data management system 2152 may include scripts or other    interpretative or executable code that identifies a series of    intermediate service requests that must be performed to the fulfill    the user's input service request. Moreover, in some embodiments, the    user's input service request may substantially identify such    intermediate steps and thereby over ride any default intermediate    service requests in the data management system 2152. In particular,    the user service request input may be declarative in nature, wherein    the user input identifies what is to be performed in as much detail    as desired, and the system 2152 determines the mapping between a    desired output and the one or more service requests that need to be    fulfilled in order to fulfill the user's request. Thus, for each    service request for which the platform 2004 is responsible for    processing, the system 2152 includes, e.g., a script, schema or    other data structure indicating the services to be activated, and    any sequencing of those services. Note that by providing such data    structures (e.g., service request scripts) so that they are    accessible by the platform 2004, the following advantages are    obtained: (1) any backup or alternative services that can be used    may be performed as necessary without the users 2004 having to    specify such alternatives; (2) network and/or service request    enhancements may be more easily utilized in fulfilling certain    service requests; e.g., certain location based service requests may    require a particular location accuracy and such accuracy may require    activating more than one location service provider. Typically, the    wireless location gateway or location center 142 would provide such    functionality. However, certain networks may assume such    functionality, and not utilize such a gateway, and the platform 2004    may assume such responsibility. Accordingly, such scripts for    location based services that require a predetermined accuracy may be    modified without the need to change user service request inputs to    the platform 2004. Thus, a location based dating service may require    location based information of mobile stations 140 that are within 20    meters of one another, and it may be determined (e.g., through user    complaints) that the accuracy currently being provided is    insufficient. Thus, the corresponding script for fulfilling an    activation of the dating service request may be changed to use    additional location service providers and/or a location gateway 142    entirely transparent to the users 2008. In another example, if the    platform 2004 offers a service to obtain estimates for obtaining    discounted hotel rooms for users 2008 seeking immediate occupancy in    a relatively local geographical area (e.g., a city or within 5 miles    of the user), the script for such a service may change frequently    according to season, occupancy rates, hotels opting in or out of    such a service.

-   Step 2252: A determination is made by the applications controller    2144 as to whether there are currently sufficient network resources    available to appropriately fulfill the service request currently    being processed (more precisely, attempting to be processed).

-   Step 2256: If the result from step 2252 is negative, then in one    embodiment of the present step, the applications controller 2144    requeues the current service for examining at a later time and    commences processing another service request as the current request.    Additionally, the applications controller 2144 may issue an    allocation request to the request provisioning system 2160 to    reserve certain network resources (e.g., reserve a high bandwidth    data channel) if such is needed by the previous “current” service    that has been requeued. If the requeued service request is not    processed within a request specific amount of time, then as in the    alternative embodiment of step 2232, the user 2008 is informed of    the failure of the service request. However, in one alternative    embodiment, instead of notifying the user 2008 of failure, the user    may be notified that there is a delay in fulfilling the service    request, and the user may be provided with the option of canceling    the service request or waiting for its fulfillment.

-   Step 2260: The applications controller 2144 activates one or more    applications for fulfilling the service request currently being    processed since all the network resources it requires are available    as well as the application(s) for fulfillment of the request. For    example, the applications illustrated in FIG. 20 may be activated by    applications controller 2144, and such an activation(s) may be via    the application gateway (FIG. 21) for activating specific    applications as one of ordinary skill in the art will understand.    Note that the service request data processed by the applications    controller 2144 may be in the form of a script that the controller    2144 interprets.

-   Step 2264: In some circumstances, service requests are automatically    activated as, e.g., intermediate steps in fulfilling another service    request. Accordingly, the present step illustrates the performance    of such automatically activated service requests.

The above high level description of the processing performed by theplatform 2004 is also applicable to disaster or large scale emergencymanagement and communication such as occurs during hurricanes, floods,earthquakes, combat situations, and the like where communications andapplications may need to be modified rapidly. In particular, byproviding a standard script or schema for requesting network servicesand/or provisioning, network applications may be easily incorporatedinto embodiments of the present disclosure. For example, during ahurricane or earthquake, high call volume capacity mobile base stationsmay be required to compensate for damaged or malfunctioninggeographically fixed base stations of a wireless carrier'sinfrastructure, and/or to handle an increase in call volume. However,network services not related to disaster assistance may need to beseverely restricted, and such restrictions may be easily provided viathe platform 2004 since the applications requirements databasemanagement system 2152 (FIG. 21) to temporarily disable or restrictnon-essential network services (e.g., high bandwidth network games,etc.). Moreover, by establishing appropriate profiles for emergencyresponder personnel in the user profile repositories 2120, suchpersonnel may be able to activate network services/applications that maybe restricted from general use. So, e.g., while non-emergency requestsfor multi-point conference calls may be restricted or unavailable to thepublic in general, such network services may be available to variousemergency responder personnel. Thus, it is aspect of the presentdisclosure that authorization for accessing networkservices/applications can be selectively provided to one or more groupsof users, wherein individuals are identified as to whether they are suchgroups by accessing each individual's profile in the profilerepositories 2120. Accordingly, large numbers network users (where mostof the users are unrelated to one another at least in the sense that thenetwork services for which each has contracted is unrelated to thecontracted network services of most others) may be restricted fromaccessing certain network services, and/or allowed to access certainnetwork services dependent upon, e.g., which group of a hierarchy ofnetwork user groups with which each user is identified via his/herprofile. Moreover, it important to note that network service requestsmay by grouped into one or more groups, wherein access and/or denial ofnetwork services may depend on the user's geographic location (and/orthe location network infrastructure by which the user accesses thenetwork). For example, an MS 140 user within an area hit by a disastermay not be provided with wireless Internet service, whereas if this sameuser were in an area remote from the disaster wireless Internet servicemay be provided. Thus, in one embodiment, the following hierarchy ofnetwork service requests may be utilized (from highest priority fornetwork services to lowest priority for network services) when adisaster is declared, e.g., by a governmental entity:

-   -   (a) Emergency requests by personnel directors and supervisors        directing emergency assistance efforts related to the disaster        (such individuals having profiles for identifying themselves as        emergency personnel directors and supervisors). Note that such        directors and supervisors may be individuals in charge of        governmental and/or military operations related to the disaster;    -   (b) Emergency command center communications for directing        emergency assistance efforts related to the disaster (e.g., with        emergency responder personnel and/or emergency response centers,        e.g., PSAPs);    -   (c) Network emergency request calls by users dialing an        emergency number, e.g., 911; note that in one embodiment, the        locations of such users may be aggregated on a display device        for emergency response personnel (e.g., PSAP 911 operators) so        that emergency assistance personnel assisting one user can also        be directed to assist other nearby users also seeking emergency        assistance while such personnel reside in the area.    -   (d) Network service requests by users requesting non-emergency        network services within the disaster area (e.g., as defined by a        governmental entity). Accordingly, for each user within a        disaster area, each requested network access by the user may be        accompanied by information indicating the user is in the        disaster area (e.g., the identification of the primary base        station with which the user is communicating) so that the        request can be identified as having relatively low priority.        Additionally, a user outside of the disaster area that is        requesting access to network resources in the disaster area may        be prevented or delayed from doing so. For example, if the last        known wireless coverage area of a user being called is in the        disaster area (as, e.g., identified in the called user's home        location register or visitor location register), then the call        may be given a relatively low priority.

Thus, it is an aspect of the present disclosure that within a disasterarea, network allocation may be driven at least partially bygeographical location of network resources being requested.

Additional processing capabilities that various embodiments of theplatform 2004 will now be described:

-   -   (a) billing system 2140: Note that in one embodiment of the        platform 2004, the billing system 2140 (or an enhancement        thereto) is the billing system of the wireless carrier with whom        the user 2008 subscribes for wireless services. It is        contemplated that for various wireless applications, and        particularly location based applications, such applications can        be more quickly made available to subscribers 2008 if the        already existing network infrastructure and support services        (such as billing) are used. Thus, assuming an appropriate and        preferably uniform interface between service request fulfillment        application management processes (not shown) and the billing        system 2140 is provided, business rules, charges for existing,        new and removed application services maybe communicated to the        billing system 2140. Furthermore, such a central billing system        2140 makes it easier for network services, and in particular,        complex network services such as location based services to be        bundled or packaged together and potentially provided under the        trademarks or servicemarks of the wireless carrier even though        such “private label” applications (identified in FIG. 20 by the        components labeled 2020 and 2024) are owned and operated by        third parties. Moreover, such a central billing system 2140 also        has the advantage of providing fewer individual bills to the        subscribers 2008 in that charges for such services may be        incorporated into the bill provided by the subscriber's wireless        carrier;    -   (b) data exposure engine (FIG. 21): This component provides the        functionality described in the Wireless Application Platform        Services and Architecture section of the Summary entitled “data        exposure processing”.

Wireless Location Applications

Such wireless location applications as were briefly described above inreference to the gateway 142 will now be described in further detail.Note that the following location related services are considered withinthe scope of the wireless location capabilities disclosed herein, andsuch services can, in general, be provided without use of a gateway 142,albeit, e.g., in a likely more restricted context wherein not allavailable wireless location estimating techniques are utilized, and/orby multiplying the number of interfaces to geolocation service providers(e.g., distinct wireless location interfaces are provided directly toeach wireless location service provider utilized).

Routing Applications Routing For Personal Services

In one noteworthy routing application, hotels and other personal serviceproviders, such as auto rental agencies, resorts and cruise ships mayprovide inexpensive or free wireless concierge services to theircustomers, wherein an inexpensive MS 140 can offered to customers thatcan be used substantially only for contacting: (i) the personal service,(ii) emergency services, (iii) receiving directions to return to thepersonal service, and/or (iv) routing or directing customerspredetermined locations such as historic sites, shopping areas, and/orentertainment. In a similar fashion, instead of providing such adedicated MS 140, the personal service could in an alternativeembodiment, allow customers access such information from their ownpersonal mobile stations 140. In one embodiment, this may beaccomplished by allowing a user to attach such information to their userprofiles and thereby obtain at least temporary access to a wirelessconcierge providing one or more of the location based services (i)-(iv)immediately above. Accordingly, the MS 140 may be wirelessly locatedduring operations (ii) and (iii) via wireless communications between theMS 140 and a local commercial wireless service provider wherein arequest to locate the MS 140 is provided to, e.g., the gateway 142, andthe resulting MS location estimate is: (1) provided to a public safetyemergency center (e.g., E911) for dispatching emergency services, or (2)provided to a mapping and routing system such as provided by Mapinfo ordisclosed in the LeBlanc et. al. patent application filed Jan. 22, 1999and having U.S. Pat. No. 6,236,365 (which is fully incorporated hereinby reference) so that the MS 140 user may be routed safely andexpeditiously to a predetermined location of the personal service. Notethat data representing the location of the personal service can beassociated with an identification of the MS 140 so that MS activationfor (iii) above results in one or more audio and/or visual presentationsof directions for directing the user to return to the personal service.

Additionally, directions to such personal services may be made availableto the personal MS 140 of a user, wherein upon calling a number (oraccessing a website via the MS), the directions to a desired destinationmay be transmitted to the MS and presented to the user. Moreover, suchdirections may be dependent upon how the MS user is traveling. Forexample, if it is known (or presumed) that the user is in a vehicle suchas an auto, the user may be directed first to a parking garage ratherthan to the front door of a government agency building. Alternatively,if it is known (or presumed) that the user is on foot, then the MS usermay indeed be directed to the front door of the government agencybuilding. Similarly, if the MS 140 is determined to be on a train,bicycle, watercraft, etc. such modes of conveyance may be used indetermining an appropriate route to present to the MS user. In oneembodiment of the present disclosure, traffic congestion may also beused to determine an appropriate route to present to the MS user.

Moreover, it is an aspect of the present disclosure that the MS 140 usermay be tracked by, e.g., periodic MS location determinations, until theMS user is substantially at the personal service. Note that if the MS140 user does not correctly follow the directions received, then for apredetermined deviation (e.g., dependent upon whether it is perceivedthat the user is on foot or in a vehicle, which may be determinedaccording to the user's velocity and/or acceleration) the MS user may bealerted to the deviation and a new route determined dependent upon,e.g., the user's new location, the direction that the user is traveling,and/or the mode of transportation. For example, if the MS 140 user goton an subway train, then after one or more locations of the MS user havebeen performed, if such locations are sufficiently accurate, it can bedetermined whether the user is proceeding along a route consistent withdirections provided, and that the user is on the subway. In the casewhere the MS user got onto the wrong subway train, the user can bealerted of this fact and given the opportunity to have a new routedetermined which takes into account not only the user's location, butwhere the user can exit the subway train, and likely, the subway trainschedules for expeditiously getting the MS user to his/her destination.

Tracking at Predetermined Times/Schedules

A tracking application for the MS 140 and the MS location providingwireless network (e.g., a CMRS, a PSTN 124 or the Internet 468) may alsoprovide the MS user with the ability to explicitly request to besubstantially continuously tracked, wherein the MS tracked locations arestored for access by those having permission (e.g., the user, parentsand/or associates of the user). Additionally, the velocity and/orexpected time of arrival at a predetermined destination may be derivedfrom such tracking and may be provided to the user or his/her associates(e.g., employer, friends, and/or family). Further, note that thistracking and notification of information obtained therefrom may beprovided via a commercial telephony or Internet enabled mobile station,or a mobile station in operable communication with a short messagingservice. For example, the MS registered owner may provide the trackingapplication permissions for those able to access such MS trackinginformation so that such information can be automatically provided tocertain associates and/or provided on request to certain associates.Additionally, note that the tracking application may also allow the MSuser to deactivate such MS tracking functionality. In one embodiment, anMS user may activate such tracking for his/her MS 140 during workinghours and deactivate such tracking during non-working hours.Accordingly, an employer can then track employee's whereabouts duringwork hours, while the employee is able to retain his/her locationprivacy when not working although the employer may be still able tocontact the employee in case of an emergency during the employee'snon-working time. Note, that this location capability and method ofobtaining location information about an MS user while assuring privacyat other times may be useful for appropriately monitoring personnel inthe military, hospitals, transportation services (e.g., for couriers,bus and taxis drivers), telecommunications personnel, emergency rescueand correctional institution personnel. Further, note that thisselective MS location capability may be performed in a number of ways.For example, the MS 140 and/or the tracking application may activate anddeactivate such tracking by dialing a predetermined number (e.g., bymanually or speed dialing the number) for switching between activationof a process that periodically requests a wireless location of the MS140 from, e.g., the location gateway 142. Note that the resulting MSlocation information from the tracking application may be made availableto other users at a predetermined phone number, Internet address and/orhaving sufficient validation information (e.g., a password).Alternatively, the tracking application may automatically activate suchMS tracking for predetermined times of the day and for predetermineddays of the week. Note that this latter embodiment may be particularlyuseful for both tracking employees, e.g., at large construction sites,and, e.g., determining when each employee is at his/her work site. Thus,in this embodiment, the tracking application may provide databasestorage of times and days of the week for activation and deactivation ofthis selective MS tracking capability that is accessible via, e.g., anetwork service control point 104 (or other telephony network controlpoints as one skilled in the art will understand), wherein triggers maybe provided within the database for generating a network message (to,e.g., a wireless location gateway) requesting the commencement oftracking the MS 140 or the deactivation of such tracking. Accordingly,the resulting MS location information may be provided to an employer'stracking and payroll system so that the employer is able to determinethe actual time an employee arrives at and leaves a work location site.

In another routing related application of the present disclosure, an MS140 and the MS location providing wireless network may provide the MSuser with functionality to register certain locations so that datarepresenting such locations can be easily accessed for use at a latertime. For example, the MS 140 user may be staying at a hotel in anunfamiliar area. Accordingly, using the present capability of thedisclosure, the user can request, via his/her MS 140, that his/herlocation at the hotel be determined and registered so that it isavailable at a later time for routing the user back to the hotel. Infact, the user may have personal location registrations of a pluralityof locations in various cities and countries so that when traveling theuser has wireless access to directions to preferred locations such ashis/her hotel, preferred restaurants, shopping areas, scenic areas,rendezvous points, theatres, athletic events, churches, entertainmentestablishments, locations of acquaintances, etc. Note, that suchpersonal location registration information may reside primarily on theuser's subscriber network, but upon the MS user's request, his/herpersonal location registrations may be transmitted to another networkfrom which the user is receiving wireless services as a roamer.Moreover, any new location registrations (or deletions) may beduplicated in the user's personal registration of the user's subscribernetwork. However, in some instances an MS user may wish to retain suchregistered locations only temporarily while the user is in a particulararea; e.g., a predetermined network coverage area. Accordingly, the MSuser may indicate (or such may be the default) that a new personallocation registration be retained for a particular length of time,and/or until a location of the user is outside the area to which suchnew location registrations appear to be applicable. However, prior todeleting any such registrations, the MS user may be queried to confirmsuch deletions. For example, if the MS user has new locationregistrations for the Dallas, Tex. area, and the MS user subsequentlytravels to London, then upon the first wireless location performed bythe MS user for location registration services, the MS user may bequeried as to whether to save the new Dallas, Tex. locationregistrations permanently, for an particular length of time (e.g. 30days), or delete all or selected portions thereof.

Other routing related applications of the present disclosure are forsecurity (e.g., tracking how do I get back to my hotel safely), and,e.g., sight seeing guided tour where the is interactive depending onfeedback from users

Tracking at Predetermined Times/Schedules

The MS 140 and the MS location providing wireless network (e.g., a CMRS,a PSTN 124 or the Internet 468) may also provide the MS user with theability to explicitly request to be substantially continuously tracked,wherein the MS tracked locations are stored for access by those havingpermission (e.g., the user, parents and/or associates of the user).Additionally, the velocity and/or expected time of arrival at apredetermined destination may be derived from such tracking and may beprovided to the user or his/her associates (e.g., employer, friends,and/or family). Further, note that this tracking and notification ofinformation obtained therefrom may be provided via a commercialtelephony or Internet enabled mobile station, or a mobile station inoperable communication with a short messaging service. For example, theMS registered owner may provide permissions for those able to accesssuch MS tracking information so that such information can beautomatically provided to certain associates and/or provided on requestto certain associates. Additionally, note that the MS 140 and the MSlocation providing wireless network may also allow the MS user todeactivate such MS tracking functionality. In one embodiment, an MS usermay activate such tracking for his/her MS 140 during working hours anddeactivate such tracking during non-working hours. Accordingly, anemployer can then track employee's whereabouts during work hours, whilethe employee is able to retain his/her location privacy when not workingalthough the employer may be still able to contact the employee in caseof an emergency during the employee's non-working time. Note, that thislocation capability and method of obtaining location information aboutan MS user while assuring privacy at other times may be useful forappropriately monitoring personnel in the military, hospitals,transportation services (e.g., for couriers, bus and taxis drivers),telecommunications personnel, emergency rescue and correctionalinstitution personnel. Further, note that this selective MS locationcapability may be performed in a number of ways. For example, the MS 140may activate and deactivate such tracking by dialing a predeterminednumber (e.g., by manually or speed dialing the number) for switchingbetween activation of a process that periodically requests a wirelesslocation of the MS 140 from, e.g., the location gateway 142. Note thatthe resulting MS location information may be made available to otherusers at a predetermined phone number, Internet address and/or havingsufficient validation information (e.g., a password). Alternatively, theMS location providing wireless network may automatically activate suchMS tracking for predetermined times of the day and for predetermineddays of the week. Note that this latter embodiment may be particularlyuseful for both tracking employees, e.g., at large construction sites,and, e.g., determining when each employee is at his/her work site. Thus,in this embodiment, the MS location providing wireless network mayprovide database storage of times and days of the week for activationand deactivation of this selective MS tracking capability that isaccessible via, e.g., a network service control point 104 (or othertelephony network control points as one skilled in the art willunderstand), wherein triggers may be provided within the database forgenerating a network message (to, e.g., the gateway 142) requesting thecommencement of tracking the MS 140 or the deactivation of suchtracking. Accordingly, the resulting MS location information may beprovided to an employer's tracking and payroll system so that theemployer is able to determine the actual time an employee arrives at andleaves a work location site.

Register Locations for Later Routing Thereto

In another routing related application of the present disclosure, an MS140 and the MS location providing wireless network may provide the MSuser with functionality to register certain locations so that datarepresenting such locations can be easily accessed for use at a latertime. For example, the MS 140 user may be staying at a hotel in anunfamiliar area. Accordingly, using the present capability of thedisclosure, the user can request, via his/her MS 140, that his/herlocation at the hotel be determined and registered so that it isavailable at a later time for routing the user back to the hotel. Infact, the user may have personal location registrations of a pluralityof locations in various cities and countries so that when traveling theuser has wireless access to directions to preferred locations such ashis/her hotel, preferred restaurants, shopping areas, scenic areas,rendezvous points, theatres, athletic events, churches, entertainmentestablishments, locations of acquaintances, etc. Note, that suchpersonal location registration information may reside primarily on theuser's subscriber network, but upon the MS user's request, his/herpersonal location registrations may be transmitted to another networkfrom which the user is receiving wireless services as a roamer.Moreover, any new location registrations (or deletions) may beduplicated in the user's personal registration of the user's subscribernetwork. However, in some instances an MS user may wish to retain suchregistered locations only temporarily while the user is in a particulararea; e.g., a predetermined network coverage area. Accordingly, the MSuser may indicate (or such may be the default) that a new personallocation registration be retained for a particular length of time,and/or until a location of the user is outside the area to which suchnew location registrations appear to be applicable. However, prior todeleting any such registrations, the MS user may be queried to confirmsuch deletions. For example, if the MS user has new locationregistrations for the Dallas, Tex. area, and the MS user subsequentlytravels to London, then upon the first wireless location performed bythe MS user for location registration services, the MS user may bequeried as whether to save the new Dallas, Tex. location registrationspermanently, for an particular length of time (e.g. 30 days), or deleteall or selected portions thereof.

Other routing related applications of the present disclosure are forsecurity (e.g., tracking how do I get back to my hotel safely), and,e.g., sight seeing guided tour where there is interactivity depending onfeedback from users.

Roaming Services

Roaming application for providing services such as wireless conciergeservices that may offered to travelers by, e.g., hotels, resorts, themeparks, and/or ski areas. Additionally and/or alternatively, a user 2008may be able to store and associate a location with a user inputdescription (and possibly a picture if the user's MS 140 supports such)and store such information so that it is available at a later time,e.g., when the user is once again in the same geographical area.

There may also be roaming services provided by an application whereinthe various portions of the user's profile and/or attachments theretomay become active depending on the geographical location of the user.For example, a hotel chain may offer regional and/or global wirelessconcierge services wherein local location based information, such aspre-selected restaurants, shopping areas, points of interest,entertainment, exercise areas, travel routes, bus (train or boat)schedules, parking areas (e.g., that may be subsidized by the hotelchain), sports equipment rentals, emergency services (police, fire,etc.), that is in a geographical area (such as a metropolitan area, aresort area, a theme park or other relatively local area) where the useris located is automatically activated as the “current” set of locationsto receive priority when the user enters a request that can be satisfiedby entities identified in such local location based information. Notethat a potentially simple embodiment of this aspect of the presentdisclosure may be for the hotel chain to have an Internet website havingfor each of their hotels, corresponding web pages dedicated to locallocation based information in geographic areas surrounding the hotel.Such web pages may provide searching and routing capabilities related tothe local location base information for relatively local geographicalareas surrounding the hotel and these web pages may be made the defaultwireless concierge service capability. In one embodiment, a user'sprofile (or specific portions thereof) maintained, e.g., (i) by anetwork service, such as a wireless carrier, (ii) by the user himself(i.e., on the user's MS 140, assuming the user's MS 140 has sufficientstorage capacity), (iii) by an electronic yellow pages entity, (iv) byan Internet search engine, may be made available (at least temporarily)to the hotel's Internet wireless concierge capabilities so that userservice requests can be easily customized to the user's preferences.Moreover, such Internet access may provide access (at least while theuser is staying at the hotel) to discounts, coupons, and/or free accessto various local facilities.

Advertising Applications

Advertising may be directed to an MS 140 according to its location. Inat least some studies it is believed that MS 140 users do not respondwell to unsolicited wireless advertisement whether location based orotherwise. However, in response to certain user queries for locallyavailable merchandise, certain advertisements may be viewed as morefriendly. Thus, by allowing an MS user to contact, e.g., a wirelessadvertising portal by voice or via wireless Internet, and describecertain products or services desired (e.g., via interacting with anautomated speech interaction unit), the user may be able to describe andreceive (at his/her MS 140) audio and/or visual presentations of suchproducts or services that may satisfy such a user's request. Forexample, a user may enter a request: “I need a Hawaiian shirt, who hassuch shirts near here?”

In the area of advertising, the present disclosure has advantages bothfor the MS user (as well as the wireline user), and for product andservice providers that are nearby to the MS user. For instance, an MSuser may be provided with (or request) a default set of advertisementsfor an area when the MS user enters the area, registers with a hotel inthe area, or makes a purchase in the area, and/or requests informationabout a particular product or service in the area. Moreover, there maybe different collections of advertisements for MS users that arebelieved to have different demographic profiles and/or purposes forbeing in the area. Accordingly, an MS whose location is being determinedperiodically may be monitored by an advertisement wizard such that thiswizard may maintain a collection of the MS user's preferences, and needsso that when the MS user comes near a business that can satisfy such apreference or need, then an advertisement relating to the fulfillment ofthe preference or need may be presented to the MS user. However, it isan aspect of the disclosure that such potential advertisingpresentations be intelligently selected using as much information aboutthe user as is available. In particular, in one embodiment of thedisclosure MS user preferences and needs may be ordered according toimportance. Moreover, such user preferences and needs may be categorizedby temporal importance (i.e., must be satisfied within a particular timeframe, e.g., immediately, today, or next month) and by situationalimportance wherein user preferences and needs in this category are lesstime critical (e.g., do not have to be satisfied immediately, and/orwithin a specified time period), but if certain criteria are met theuser will consider satisfying such a preference or need. Thus, finding aChinese restaurant for dinner may be in the temporal importance categorywhile purchasing a bicycle and a new pair of athletic shoes may beordered as listed here in the situational category. Accordingly,advertisements for Chinese restaurants may be provided to the user atleast partially dependent upon the user's location. Thus, once such arestaurant is selected and routing directions are determined, then theadvertising wizard may examine advertisements (or other availableproduct inventories and/or services that are within a predetermineddistance of the route to the restaurant for determining whether there isproduct or service along the route that could potentially satisfy one ofthe user's preferences or needs from the situational importancecategory. If so, then the MS user may be provided with the option ofexamining such product or service information and registering thelocations of user selected businesses providing such products orservices. Accordingly, the route to the restaurant may be modified toincorporate detours to one or more of these selected businesses. Theflowchart of FIGS. 23A and 23B provides steps that illustrate themodification (if necessary) of such a route so that the MS user canvisit one or more locations along the route for accessing one or moreadditional products or services.

Of course, an MS user's situationally categorized preferences and needsmay allow the MS user to receive unrequested advertising during othersituations as well. Thus, whenever an MS user is moving such anadvertisement wizard (e.g., if activated by the user) may attempt tosatisfy the MS user's preferences and needs by presenting to the useradvertisements of nearby merchants that appear to be directed to suchuser preferences and needs.

Accordingly, for MS user preferences and needs, the wizard will attemptto present information (e.g., advertisements, coupons, discounts,product price and quality comparisons) related to products and/orservices that may satisfy the user's corresponding preference or need:(a) within the time frame designated by the MS user when identified ashaving a temporal constraint, and/or (b) consistent with situationalcriteria provided by the MS user (e.g., item on sale, item is less thana specified amount, within a predetermined traveling distance and/ortraveling time) when identified as having a situational constraint.Moreover, such information may be dependent on the geolocation of boththe user and a merchant(s) having such products and/or services.Additionally, such information may be dependent on a proposed orexpected user route (e.g., a route to work, a trip route). Thus, itemsin the temporal category may be ordered according to how urgent must apreference or need must be satisfied, while items in the situationalcategory may be substantially unordered and/or ordered according todesirableness (e.g., an MS user might want a motorcycle of a particularmake and maximum price, but want a new car more). However, since itemsin the situational category may be fulfilled by substantiallyserendipitous circumstances detected by the wizard, various orderings orno ordering may be used. Thus, e.g., if the MS user travels from onecommercial area to another, the wizard may compare a new collection ofmerchant products and/or services against the items on an MS user'stemporal and situational lists, and at least alerting the MS user thatthere may be new information available about a user desired service orproduct which is within a predetermined traveling time from where theuser is. Note that such alerts may be visual (e.g., textual, or iconic)displays, or audio presentations using, e.g., synthesized speech (suchas “Discounted motorcycles ahead three blocks at Cydes Cycles”).

Electronic Yellow Pages

Note that the advertising aspects of the present disclosure may beutilized by an intelligent electronic yellow pages which can utilize theMS user's location (and/or anticipated locations; e.g., due to roadwaysbeing traversed) together with user preferences and needs (as well asother constraints) to both intelligently respond to user requests aswell as intelligently anticipate user preferences and needs. A blockdiagram showing the high level components of an electronic yellow pagesaccording to this aspect of the present disclosure is shown in FIG. 19.Accordingly, in one aspect of the present disclosure advertising is userdriven in that the MS user is able to select advertising based onattributes such as: merchant proximity, traffic/parking conditions, theproduct/service desired, quality ratings, price, user merchantpreferences, product/service availability, coupons and/or discounts.That is, the MS user may be able to determine an ordering ofadvertisements presented based on, e.g., his/her selection inputs forcategorizing such attributes. For example, the MS user may requestadvertisements of athletic shoes be ordered according to the followingvalues: (a) within 20 minutes travel time of the MS user's currentlocation, (b) midrange in price, (c) currently in stock, and (d) nopreferred merchants. Note that in providing advertisements according tothe MS user's criteria, the electronic yellow pages may have to makecertain assumptions such if the MS user does not specify a time forbeing at the merchant, the electronic yellow pages may default the timeto a range of times somewhat longer than the travel time thereby goingon the assumption that MS user will likely be traveling to an advertisedmerchant relatively soon. Accordingly, the electronic yellow pages mayalso check stored data on the merchant (e.g., in the merchant profile &location database of FIG. 19) to assure that the MS user can access themerchant once the MS user arrives at the merchant's location (e.g., thatthe merchant is open for business). Accordingly, the MS user maydynamically, and in real time, vary such advertising selectionparameters for thereby substantially immediately changing theadvertising being provided to the user's MS. For example, the MS displaymay provide an area for entering an identification of a product/servicename wherein the network determines a list of related or complementaryproducts/services. Accordingly, if an MS user desires to purchase awedding gift, and knows that the couple to be wed are planning a trip toAustralia, then upon the MS user providing input in response toactivating a “related products/services” feature, and then inputting,e.g., “trip to Australia” (as well as any other voluntary informationindicating that the purchase is for: a gift, for a wedding, and/or aprice of less than $100.00), then the intelligent yellow pages may beable to respond with advertisements for related products/services suchas portable electric power converter for personal appliances that isavailable from a merchant local (and/or non-local) to the MS user.Moreover, such related products/services (and/or “suggestion”)functionality may be interactive with the MS user. For example, theremay be a network response to the MS user's above gift inquiry such as“type of gift: conventional or unconventional?”. Moreover, the networkmay inquire as to the maximum travel time (or distance) the MS user iswilling to devote to finding a desired product/service, and/or themaximum travel time (or distance) the MS user is willing to devote tovisiting any one merchant. Note that in one embodiment of the electronicyellow pages, priorities may be provided by the MS user as to apresentation ordering of advertisements, wherein such ordering may beby: price, quality, convenience to purchase, language spoken at themerchant, user safety concerns in traveling to or being at themerchant's location, etc

Note that various aspects of such an electronic yellow pages describedherein are not constrained to using the MS user's location. In general,the MS user's location is but one attribute that can be intelligentlyused for providing users with targeted advertising, and importantly,advertising that is perceived as informative and/or addresses currentuser preferences and needs. Accordingly, such electronic yellow pageaspects of the present disclosure are not related to a change in the MSuser's location over time also apply to stationary communicationstations such home computers wherein, e.g., such electronic yellow pagesare accessed via the Internet. Additionally, the MS user may be able toadjust, e.g., via iconic selection switches (e.g., buttons or toggles)and icon range specifiers (e.g., slider bars) the relevancy and acorresponding range for various purchasing criteria. In particular, oncea parameter is indicated as relevant (e.g., via activating a toggleswitch), a slider bar may be used for indicating a relative or absolutevalue for the parameter. Thus, parameter values may be for:product/service quality ratings (e.g., display given to highestquality), price (low comparable price to high comparable price), traveltime (maximum estimated time to get to merchant), parking conditions.

Accordingly, such electronic yellow pages may include the followingfunctionality:

-   -   (a) dynamically change as the user travels from one commercial        area to another when the MS user's location is periodically        determined such that local merchant's are given preference;    -   (b).routing instructions are provided to the MS user when a        merchant is selected;    -   (c) provide dynamically generated advertising that is related to        an MS user's preferences or needs. For example, if an MS user        wishes to purchase a new dining room set, then such an        electronic yellow pages may dynamically generate advertisements        (e.g., via the ad generation component of the merchant ad        management system of FIG. 19) with dining room sets therein for        merchants that sell them. Note that this aspect of the present        disclosure is can be accomplished by having, e.g., a        predetermined collection of advertising templates (e.g., in the        merchant ad template database, FIG. 19) that are assigned to        particular areas of an MS user's display wherein the advertising        information is selected according to the item(s) that the MS        user has expressed a preference or desire to purchase, and        additionally, according to the user's location, the user's        preferred merchants, and/or the item's price, quality, as well        as coupons, and/or discounts that may be provided. Thus, such        displays may have a plurality of small advertisements that may        be selected for hyperlinking to more detailed advertising        information related to a product or service the MS user desires.        Note that this aspect of the present disclosure may, in one        embodiment, provide displays (and/or corresponding audio        information) that is similar to Internet page displays. However,        such advertising may dynamically change with the MS user's        location such that MS user preferences and needs for an item(s)        (including services) having higher priority are given        advertisement preference on the MS display when the MS user        comes within a determined proximity of the merchant offering the        item. Moreover, the MS user may be able dynamically reprioritize        the advertising displayed and/or change a proximity constraint        so that different advertisements are displayed. Furthermore, the        MS user may be able to request advertising information on a        specified number of nearest merchants that provide a particular        category of products or services. For example, an MS user may be        able to request advertising on the three nearest Chinese        restaurants that have a particular quality rating. Note, that        such dynamically generated advertising    -   (d) information about MS users' preferences and needs may be        supplied to yellow page merchants regarding MS users who reside        and/or travel nearby yellow subscriber merchant locations as        described hereinabove

FIG. 19 (Block Diagram of Electronic Yellow Pages)

The following is a high level description of some of the componentsshown in FIG. 19 of an illustrative embodiment of the electronic yellowpages of the present disclosure.

-   -   a. Electronic yellow pages center: Assists both the users and        the merchants in providing more useful advertising for enhancing        business transactions. The electronic yellow pages center may be        a regional center within the carrier, or (as shown) an        enterprise separate from the carrier. The center receives input        from users regarding preferences and needs which are first        received by the user interface.    -   b. User interface: Receives input from a user that validates the        user via password, voice identification, or other biometric        capability for identifying the user. Note that the        identification of the user's communication device (e.g., phone        number) is also provided. For a user contact, the user interface        does one of: (a) validates the user thereby allowing user access        to further electronic yellow page services, (b) requests        additional validation information from the user, or (c)        invalidates the user and rejects access to electronic yellow        pages. Note that the user interface retrieves user        identification information from the user profile database        (described hereinbelow), and allows a validated user to add,        delete, and/or modify such user identification information.    -   c. User ad advisor: Provides user interface and interactions        with the user. Receives an identification/description of the        user's communication device for determining an appropriate user        communication technique. Note that the user ad advisor may also        query (any) user profile available (using the user's identity)        for determining a preferred user communication technique        supported by the user's communication device. For example, if        the user's communication device supports visual presentations,        then the user ad advisor defaults to visual presentations unless        there are additional constraints that preclude providing such        visual presentations. In particular, the user may request only        audio ad presentations, or merely graphical pages without video.        Additionally, if the user's communication device supports speech        recognition, then the user ad advisor may interact with the user        solely via verbal interactions. Note that such purely verbal        interactions may be preferable in some circumstances such as        when the user can not safely view a visual presentation; e.g.,        when driving. Further note that the user's communication device        may sense when it is electronically connected to a vehicle and        provide such sensor information to the user ad advisor so that        this module will then default to only a verbal presentation        unless the user requests otherwise. Accordingly, the user ad        advisor includes a speech recognition unit (not shown) as well        as a presentation manager (not shown) for outputting ads in a        form compatible both with the functional capabilities of the        user's communication device and with the user's interaction        preference.        -   Note that the user ad advisor communicates: (a) with the            user ad selection engine for selecting advertisements to be            presented to the user, (b) with the user profile database            for inputting thereto substantially persistent user personal            information that can be used by the user ad selection            engine, and for retrieving user preferences such as media            preference(s) for presentations of advertisements, and (c)            with the user preference and needs satisfaction agents for            instantiating intelligent agents (e.g., database triggers,            initiating merchant requests for a product/service to            satisfy a user preference or need).        -   Also note that in some embodiments of the present            disclosure, the user ad advisor may also interact with a            user for obtaining feedback regarding: (a) whether the            advertisements presented, the merchants represented, and/or            the products/services offered are deemed appropriate by the            user, and (b) the satisfaction with a merchant with which            the user has interactions. In particular, such feedback may            be initiated and/or controlled substantially by the user            preference and needs satisfaction agent management system            (described hereinbelow).    -   d. User profile database: A database management system for        accessing and retaining user identification information, user        personal information, and identification of the user's        communication device (e.g., make, model, and/or software        version(s) being used). Note that the user profile database may        contain information about the user that is substantially        persistent; e.g., preferences for: language (e.g., English,        Spanish, etc.), ad presentation media (e.g., spoken, textual,        graphical, and/or video), maximum traveling time/distance for        user preferences and needs of temporal importance (e.g., what is        considered “near” to the user), user demographic information        (e.g., purchasing history, income, residential address, age,        sex, ethnicity, marital status, family statistics such as number        of children and their ages), and merchant        preferences/preclusions (e.g., user prefers one restaurant chain        over another, or the user wants no advertisements from a        particular merchant).    -   e. User ad selection engine (also referred to as “user ad        selection” in FIG. 19): This module selects advertisements that        are deemed appropriate to the user's preferences and needs. In        particular, this module determines the categories and        presentation order of advertisements to be presented to the        user. To perform this task, the user ad selection engine uses a        user's profile information (from the user profile database), a        current user request (via the user ad advisor), and/or the        user's current geolocation (via the interface to the location        gateway 142). Thus, for a user requesting the location of an        Italian restaurant within ½ mile of the user's current location,        in a medium price range, and accepting out of town checks, the        user ad selection engine identifies the ad criteria within the        user's request, and determines the advertising categories        (and/or values thereof) from which advertisements are desired.        In one embodiment,    -   Note that the user ad selection engine can suggest advertisement        categories and/or values thereof to the user if requested to do        so.

Traveling & Ad Wizards

When an MS 140 appears to be traveling an extended distance through aplurality of areas (as determined, e.g., by recent MS locations along aninterstate that traverse a plurality of areas), then upon entering eachnew area having a new collection of location registrations (and possiblya new location registration wizard) may be provided. For example, a newdefault set of local location registrations may become available to theuser. Accordingly, the user may be notified that new temporary locationregistrations are available for the MS user to access if desired. Forexample, such notification may be a color change on a video displayindicating that new temporary registrations are available. Moreover, ifthe MS user has a personal profile that also is accessible by a locationregistration wizard, then the wizard may provide advertising for localbusinesses and services that are expected to better meet the MS user'stastes and needs. Thus, if such wizard knows that the MS user prefersfine Italian food but does not want to travel more than 20 minutes byauto from his/her hotel to reach a restaurant, then advertisements forrestaurants satisfying such criteria will become available to the userHowever, MS users may also remain anonymous to such wizards.

Note, that by retaining MS user preferences and needs, if permission isprovided, e.g., for anonymously capturing such user information, thisinformation could be provided to merchants. Thus, merchants can get anunderstanding of what nearby MS user's would like to purchase (and underwhat conditions, e.g., an electric fan for less than $10). Note suchuser's may be traveling through the area, or user's may live nearby.Accordingly, it is a feature of the present disclosure to providemerchant's with MS user preferences and needs according to whether theMS user is a passerby or lives nearby so that the merchant can bettertarget his/her advertising.

In one embodiment, a single wizard may be used over the coverage area ofa CMRS and the database of local businesses and services changes as theMS user travels from one location registration area to another.Moreover, such a wizard may determine the frequency and when requestsfor MS locations are provided to the gateway 142. For example, suchdatabases of local businesses and services may be coincident with LATAboundaries. Additionally, the wizard may take into account the directionand roadway the MS 140 is traveling so that, e.g., only businesseswithin a predetermined area and preferably in the direction of travel ofthe MS 140 are candidates to have advertising displayed to the MS user.

The flowchart of FIGS. 24A and 24B is illustrative of the stepsperformed when, e.g., MS user input of preferences and needs isiteratively examined at various user locations for determining thelocation(s) that sufficiently satisfy user specified constraints (e.g.,temporal or situational constraints) so that the user is alerted ornotified of products and/or services that satisfy the user's input. Thesteps 2004 through 2040 are fully disclosed and explained in thesections hereinabove.

Points of Interest Applications

Sight seeing or tour applications may be provided for MS users, whereinrepeated locations of the users MS is determined for assisting inrouting the user to desired, e.g., points of interest. In particular,self guided tours may be provided by such applications, wherein theapplication is interactive with the user depending on user feedback,e.g., as to one or more points of interest the user desires to see oraccess, the time the user has available to access the points ofinterest, the estimated time needed to access the points of interest,the cost of certain points of interest. Such interactivity with the usermay be verbal and/or visual, and include directions to points ofinterest according to, e.g., (i) a route that efficiently uses theuser's time (e.g., least travel time plus user time expected waiting toaccess points of interest upon arriving), (ii) a route that is expectedto reduce the cost of accessing the points of interest (e.g., a lessexpensive Monday matinee presentation/play as opposed to a Fridayshowing of the same), (iii) a route that must rendezvous with othersand/or at be at a predetermined location at a particular time, (iv) aroute that is to avoid a particular area, or location (e.g., due tocrime, bad weather, poor services/accomodations, etc., and optionallyavoidance during a particular, time of day), (v) a route may bedynamically modified as circumstances change (e.g., lengthy delay at onepoint of interest precludes visitation of a second point of interest andpossibly replaced by a different point of interest, or causes the secondpoint of interest visitation to be posponed), and/or (vi) a route withalternative points of interest wherein the user is routed to a subset ofsuch points of interest depending on other criteria, e.g., the criteriaaccording to (i)-(v) above.

Picture/Video Applications

An application may provided for MSs that have photo/video capabilitiesintegrated therein, wherein location information indicative of where apicture/video is taken using the MS (optionally also with a time/date ofobtaining the picture/video data) is associated with the picture/video.Note that such location information may be determined from a wirelesslocation of a users MS. In particular, MS latitude-longitude coordinatesmay be transformed into a city address (or city area) together with adirection(s) from the location(s) where the picture/video was taken.

Visualization Applications Using Wireless Location

An application of a wireless location system may enable geographicvisualization applications, wherein one or more geographic areas ofinterest are presented as visual geographic images or maps withannotations thereon indicative of, e.g., a relative interest a mobilestation user may have in such geographic areas. In particular, suchgeographic areas may be color coded on a map according to an expectedinterest the user may have in different ones of the areas. For example,a mobile station user may be desirous of finding a parking space in alarge parking facility such as at an airport parking facility, municipalparking (on, e.g., downtown streets or parking garages), or a shoppingmall. If the parking facility has electronic monitoring for monitoringparking spaces therein, then parking spaces (e.g., for automobiles orother modes of transportation) can be readily identified as beingoccupied or available via such electronic monitoring so that a mobilestation user can view on his/her mobile station a map of the parkingfacility with a designated color (e.g., bright green) identifying one ormore nearby available parking spaces, and optionally providing a routeto one of the parking spaces. Of course, there may be no guarantee thatthe user will arrive at one of the parking spaces prior to it beingtaken by someone else. However, if another takes the parking space, thenthe user can be notified of the parking space's unavailabilitypotentially substantially before travelling to the un available parkingspace. Note that notifications of available parking spaces in real time(or nearly so) can be provided by, e.g., marking a center of eachparking space with a distinctive insignia or design that can be readilyidentified via video input from one or more electronic monitoringdevices that view the parking spaces. In particular, when a parkingspace is available, the insignia or design on the parking space isvisible to one of the video monitors, and when an automobile (or othervehicle) is parked in the parking space, the insignia or design on theparking space is at least partially occluded (more preferably,substantially occluded). Accordingly, such video input can be providedto computational equipment for recognizing the predetermined insignia(s)or design(s) painted, taped or otherwise attached to the parking spaces.Such symbol recognition computational devices may be modified versionsof bar code readers, or, e.g., techniques as disclosed in U.S. Pat. No.7,274,823 by Lane, which is fully incorporated herein by reference,wherein symbols embedded in digital video signals are recognized.

Of course, in providing parking space information to the user, both thelocation of an empty parking space and the users location preferablyshould be known or determined so that the user may be navigated to anempty parking space. In addition to a service for locating such emptyparking spaces for users in, e.g., parking garages, shopping malls,street parking in downtown areas, etc., other services may also beprovided which rely on wirelessly locating mobile station users and/orthe resources for such users. In particular, such users may requestnotifications for assisting in locating other resources such as a nearbyrestaurant having a reduced (or no) wait time for service, a hotel ormotel having a vacancy, a campsite at a campground, a theme park (orother) attraction having a reduced (or no) wait time.

The following high level pseudo-code is a simplified illustration of theprocessing performed regarding user notification of: (1) availableresources that cannot be typically reserved prior to actual use, such asavailable parking spaces, available campsites, available gaminglocations (at a machine or gaming table) in a casino, and/or (2)resources (e.g., restaurants, theme park attractions, conventionpresentations) that are determined to require less user time to accessthan other similar resources.

User activates, at his/her mobile station (e.g., MS 140, or merely MSherein), an application (APP) that  provides notifications of anavailability of one or more resources of interest to the user, at one ormore  geographical locations of interest to the user; If not previouslyauthorized, the user authorizes the application to wirelessly locate theMS; Put an identification of the user (or the MS) on a queue of userswaiting for one of the resources; The application APP periodicallycommences requesting wireless locations of the MS at a frequency dependent upon, e.g., an expected or appropriate speed of the MS,and/or a change in direction of the  MS, and an expected change in theavailability of the resources; While (an MS wireless location isperiodically received) AND  (the MS is in proximity for still seeking anavailable resource) AND  (there has been no termination of theapplication APP by the MS user in seeking one of the resources)  AND (aresource has not been allocated to the MS, more particularly, the userthereof) DO { /* However, when (a resource has been allocated to the MS,more particularly, to the user thereof) OR  (all resources becomeunavailable) independently of the processing of this “While” loop, theninterrupt  “While” loop processing, rollback any resource allocationmade in this loop to the user, dequeue the  user, and exit this loopimmediately */ For each most recent wireless location of the MS receivedDO {    AvailResources ← Obtain locations of the currently availableresources, wherein these     locations are up dated when there is achange in the status of the currently available     resources;     /*the terms “available” and “availability” may be understood as: (1)indicative of an output      providing a binary (e.g., yes/no ortrue/false) result, and (2) dependent upon a      threshold number ofusers that can be effectively supported by the resource (e.g., up     to a predetermined threshold number of users can be appropriatelysupported by the      resource simultaneously or during a time interval,but the resource degrades, fails,      and/or is not appropriatelyeffective when the number of users for the resource      exceeds thepredetermined threshold number. */    If (SIZEOF(AvailResources) iszero) then    {  If (there is no active timer running to preventnotification) then {      transmit a notification to the MS informingits user that no resources are currently       available;      If(received user input indicates the user wants APP to continue lookingfor a       resource for the user) then       Send next usernotification only when there is an available and unallocated       resource, or, a predetermined elapsed time of a timer (activatedhere) has        expired, e.g., 3 minutes;      }     Else Exit Whileloop;    } ElseIf (all resources are allocated, but at least one isavailable) then    {  If (there is no active timer running to preventnotification) then {      transmit a notification to the MS informingits user that a resource may be available,        but all have beenallocated;      If (received user input indicates the user wants APP tocontinue looking for a       resource for the user) then       Send nextuser notification only when there is an available and unallocated       resource, or, a predetermined elapsed time of a timer (activatedhere) has        expired, e.g., 3 minutes;      }    } ElseIf (thelocation of the user's MS is near an available and unallocated resource)AND (no      other user, that has been seeking a resource longer, is atleast as near the available      and unallocated resource) then {      allocate the resource to the user;       transmit a notificationto the MS informing its user of an available resource, and       provide directions to the resource; the notification may includeinformation        for navigating the user to the resource; suchinformation may be graphically        provided on a map showing thelocation of the user and/or the resource;       dequeue the user, butsave user's state in case user needs to be re-queued due        to theresource being taken by another before the user gets it;       deleteany active timer for the user;       }   } ENDDO } ENDDO; If (the userallocated resource becomes unavailable) AND (the user's MS is not at theresource) AND (the  user has not obtained, reserved, registered atanother one of the resources) then {   Re-queue the user withoutresetting the user's resource seek time;   GOTO the While loop above; }Note that machine instructions for embodying variations of the abovepseudo-code may be used for routing users to available gaming machinesin a casino, routing user's to available attractions in an amusement ortheme park, and/or routing user's to the most sparely populated skilifts at a ski resort.

Targeted Incentive Applications Using Wireless Location

An incentive providing application is now disclosed, wherein electroniccoupons, discounts, promotions, etc. (collectively, referred to as“incentives” herein) may be provided to the user of the mobilecommunications device, e.g. at the request of the user, and generally,for a particular product/service or product/service type. Moreover, suchan application may provide these incentives according to, the userslocation and time sensitive information in that the incentives may bedependent upon the user's geographic location, and may also havebuilt-in time constraints (e.g., an expiration time/date) which may,e.g., vary with a context indicative of such criteria as: the user'slocation, previous locations of the user, user purchasing behavior, andone or more (social) networks of contacts/friends of the user. Inparticular, the present application is directed to providing, e.g.,targeted advertising to users (e.g., also referred to as “consumers” inthe present context) by combining various technologies to provide asystem and service that:

-   -   (a) allows the consumer to become aware of a product/service in        terms of both time and location, in which the consumer shows an        interest;    -   (b) allows the system to know the at least information about the        consumer that provides some measure of predictability in terms        of what the consumer will purchase and/or has an interest        therein. Note that anonymity of the consumer may still be        maintained.    -   (c) activates techniques for obtaining information from/about        the consumer for benefiting the consumer, wherein such        information is obtained by both explicit consumer input as well        as analysis of the consumer's behavior related to contacts with        others (e.g., dissemination of incentives, as well as locations        visited by the consumer);    -   (d) provides and transmits to a consumer (e.g., via an MS        therefor) various alternatives prior to, or within a reasonable        time, of the consumer making a selection of an item to purchase        so that the consumer may benefit from such alternatives to which        the consumer is provided within a relatively short time span.        In particular, the present advertising application benefits        users/consumers by providing incentives that are more        “intelligent” or “smart” than heretofore has been provided to        users, wherein such incentives can function to both assist the        consumer in buying, as well as assisting an advertiser in        selling products in a timely and cost effective manner.

Additionally, the present incentive providing application may also beused in the identification of alternative materials, products and/orservices available to consumers and parties interested in locatingalternatives to whatever product/service in which they have demonstratedan interest or in which a provider may recognize as an opportunity tomake a presentation. For instance, a consumer who has an interest inpurchasing a particular material or design for a bathroom may, throughthe presently disclosed incentive providing application learn ofalternative materials and/or designs such as a different type of tile orfixture. Additionally, a scientist may be provided with alternativesthat he might not have otherwise recognized for a particularexperimental use. Also, a product/service provider may be provided withalternatives methods of delivering a product/service.

In one aspect of the present disclosure, a mobile communication device(also referred to herein as a “MCD” instead of an “MS” in this section)with a computational capability to execute and/or activate what isgenerally referred to as “applications” or “apps” is utilized, whereinthe MCD includes, e.g.,:

-   -   (i) an ability to be located (e.g., via built-in GPS detection        electronics, or other location capabilities whether requiring        MCD location specific electronics or not),    -   (ii) a built-in camera, e.g., of sufficient quality to        photograph bar codes, product packaging, clothing details (e.g.,        texture, composition, etc.), product model numbers, product        identification numbers, manufacturer/producer names, source of        origin, etc., and    -   (iii) in at least one embodiment, a light sensor for detecting        coherent (or otherwise) light from, e.g., a bar code scanner.    -   Given such an MCD having the features (i)-(iii) above, a        communications network application can be provided on the MCD,        wherein the communications network application coordinates and        enables various features of the MCD for obtaining information        about a user desired product or service, and subsequently        providing assistance with purchasing such a product or service,        e.g., via an incentive related to a store, or shopping center        nearby the user's location or in which the user is currently        residing. In one embodiment, a user of such an MCD, upon seeing        a product of interest, activates the communications network        application which responds with at least an option for the user        to enter information about the product or service of interest        (generically referred to as an “item” herein). Upon activating        this option, the user may, e.g., use the MCD to take series of        one or more photos of the item, its merchandising tag, a tag        identifying its manufacturer, model number, and/or its        composition. Subsequent to completion of the series of photos,        the user may add additional description (either textually,        verbally, or form-based) providing comments and/or constraints        about the item such as: (i) indicating that even though the        photos show the product in red, a preferred color would be        white, (ii) that the dress size should be size 8 rather than        6, (iii) the shirt material should be rayon rather than        cotton, (iv) a distance the user is willing to travel to view or        access the desired product, (v) characteristics (if any) of a        similar but unacceptable product, (vi) one or more preferred        manufacturers or distributors or suppliers, (vii)        pricing/financing constraints (e.g., the product must be priced        less than a certain amount, capable of being financed over at        least 6 months, etc.), (viii) warranty or return policy        constraints, and/or (ix) the item's type (e.g., resort        destination, clothing, automobile, recreational equipment,        etc.). In one embodiment, the user may assign such textual or        verbal description to locations of the photos to assist in the        description of the item of interest. Additionally/optionally,        the user may also link the photos together whereby, e.g., a        first photo shows an overall view of the item with links to        other photos being located on this first photo for showing        additional details at their respective link locations on the        first photo. Moreover, in one embodiment, the user may record a        video of the item of interest and provide such additional        description (either textually, verbally or form-based, e.g., via        a graphical MCD user interface) to facilitate identifying the        item of interest. Note that hereinbelow, both photos and videos        will be identified (to the extent possible) by the term “photo”        or “photos”.

Additionally/optionally, if the photo(s) includes one or more extraneousarticles, e.g., various displays of clothing, the user may be able tooutline or highlight (e.g., on the MCD's touch screen) the particularitem of interest to facilitate identification thereof.Alternatively/optionally, extraneous portions of the photo(s) may bedeleted (e.g., crossed out, scribbled over or erased) from the photo(s)to thereby further identify the item of interest to the user. Forexample, a user may activate the communications network application totake a photo of a person walking in New York city whose clothing is ofinterest to the user, then delete other people in the photo to therebybetter identify the clothing of interest.

Following any such user input of item photo(s), descriptions and/orconstraints, the user may then submit this item information to a remotenetwork host site (e.g., an Internet website) for identifying the userdesired product, and determining any of the following:

-   -   (a) An incentive for purchasing the item or a similar item.    -   (b) A location (or website address) of a user acceptable        provider of the item.    -   (c) A photo of the item (or similar item) currently available        for purchase by the user.    -   (d) One or more reviews or assessments of the item (or similar        item).

Providing the above information from (a) through (d) can becomputationally challenging since substantial intelligence about itemsfor purchase and/or the user may be needed to properly address all ormost inquiries. However, such computational capabilities existcurrently. For example, IBM super computers such as “Deep Blue” andvariants thereof provide sufficient computational processing power tointelligently assist very large numbers of consumers with accessing andpurchasing products/services. Moreover, such super computers are nowproficient in understanding natural language to such an extent thatappropriate inferences about what is intended (even if somewhatambiguous) can be very rapidly determined for large numbers ofconsumers. Such rapid linguistic proficiency has been demonstrated by anIBM super computer winning at the television game “Jeopardy” over thebest human “Jeopardy” players. Moreover, making such computationalcapabilities (both hardware and software) available on a communicationsnetwork, such as the Internet, via one or more network nodes,intelligent “cloud” computing can be performed for consumers wherein theconsumers use their MCD's to access (explicitly, implicitly and/orautomatically) such intelligent network nodes wherein such assistance isfor:

-   (i) Suggesting products/services that are likely to meet a consumers    needs/desires, e.g., given past behavior of the consumer, the    consumer likes and dislikes (e.g., for brand names, stores, etc.),    the consumer's time constraints, the consumer's financial    constraints, the consumer's ability to access various geographical    locations, the consumer's preferences in, e.g., acquiring items    similar to another person (e.g., clothing worn by a popular singer,    actor, etc.).-   (ii) Providing such suggestions that are consistent with the    consumer's perceived/actual constraints and/or values. For example,    a consumer may wish to purchase a new pair of shoes. Accordingly,    the consumer may enter the following information into his MCD    regarding a desire to purchase such a new pair of shoes: “size 11    men's shoe, black with rounded toe, slip on, accessible within 5    miles of my location within the next 3 weeks, preferably to access    the shoes within the time period of 6 pm to 7 pm weekdays or 12 pm    to 4 pm weekends, preferably on sale with price less than $100,    preferably by Clarke, Rockport, Florshiem, but not by Adidas.”    However, to intelligently assist this consumer, additional    information may also be necessary/appropriate. For example, the    network (Internet) node providing such consumer assistance may    additionally use further consumer related information indicative of    other constraints, preferences, values that are particular to the    consumer, such as,    -   a. preferably, alert the consumer about 1 hour before he        proceeds on an expected route (e.g., to work or to home from        work) that will take him within the 5 miles of a store having        the desired shoes;    -   b. do not provide the alert for a shoe store previously visited        unless new information is available such as: new shoe inventory,        new sale, etc.;    -   c. check the consumer's preferences to determine whether he has        raised or lowered his preference for one or more shoe stores, or        entirely filtered out one or more shoe stores. Also, raise the        preference for Nordstrom's since I have a credit at Nordstrom's.        Also, remind me

Note the application may search the Internet, e.g., web crawlers, muchas Internet search engines (e.g., Google, Yahoo, Bing do) for capturing,identifying and/or classifying information related to products,services, who is buying/selling what items, who is wearing or acquiringwhat items, what items are on sale,

The application may be configured to receive information about purchasesmade by the consumer to better assist the consumer in the future. Forexample, referring to the shoes example above, the application maydetect that the consumer has visited a particular shoe store (possiblyrepeatedly) and has not purchased any shoes, then a likelihood of buyingshoes at the store may be reduced. Accordingly, in addition to aconsumer preference for certain brands, stores, or items, theapplication disclosed herein may also use a likelihood of success factorto assist the consumer in accessing and/or purchasing desired items. Inone embodiment, both a likelihood of success factor (LSF) and a consumerpreference factor (CPF) may used for prioritizing and/or suggestingwhere/how to access/buy particular items. Moreover, additional factorsmay also be used for assisting the consumer, including: (a) a valuefactor that is indicative of a best value for the selling price of anitem, (b) a seller/buyer reliability factor (RF) that provides aquantitative indication of, e.g., seller/buyer willingness toexchange/refund and/or a promptness at delivery of items. Additionally,a risk factor may be provided that is a quantitative indication of theconsumer's tolerance for risk in buying/selling a particular item. Forinstance, Such factors as described herein are for modeling the consumerso that the application can be effective at predicting what assistancethe consumer will perceive as most valuable to him/her (e.g., related toa particular item and/or the purchase or selling thereof), andoptionally, what assistance is of little value to the consumerregarding, e.g., the purchasing or selling of a particular item.

In one embodiment, consumers may explicitly adjust the values of theabove identified factors

However, the following features may be provided by the method and systemdisclosed herein:

-   -   (a) An item in a photo may be substantially automatically (or        interactive with the user).    -   (b) For a user that is identified as being in a particular        store, the photo(s) may be matched with items for sale in the        store, and an electronic incentive may be provided or other        information may be returned to the user. For example, in large        stores with relatively few customer service personnel, a user        desired item may be unavailable in a size, color or quantity        that the user desires. In such a case, instead of hunting down a        store employee that may or may not be knowledgeable about the        availability of the desired item, the user may activate the        communications network application for taking a photo of, e.g.,        the store tag for the item and submit this photo to the host        website which, in turn, may transfer the photo (and any related        information, e.g., the user's location) to a website for the        store (or for the chain of such stores). Thus, website for the        store identifies the item by the photo of the in-store tag        identifying the item (or a related item, e.g., the in-store tag        for the desired item of a different color). Subsequently (and        possibly depending on user input), the store website may        transmit a presentation to the user showing the presumed desired        item together with one or more of the following:        -   (i) A location of another store having the desired item.        -   (ii) An electronic form for ordering the desired item from            the store website, wherein the user may pay for the desired            item via an in-store checkout or via the store website. Note            that in one embodiment, the communications network            application may automatically fill in any user specific            information needed for delivery of the desired item to the            user's home address. Moreover, an incentive may be provided            to the user since the desired item was not available for            purchase at the store. Further note that such electronic            displays provided to the user's MCD related to the purchase            of the desired item may be scanned at one of the store's            checkout stations for purchasing the desired item. In            particular, information from the store's website regarding            the desired item, e.g., a bar code, displayed on the MCD's            display may be scanned for confirming purchase of the            desired item from the website wherein the desired item is to            be provided to the user at a later date. Accordingly, this            aspect of the present disclosure may assist in reducing            in-store customer support personnel while at the same time            providing more effective responses to customers.        -   (iii) In the case that the user transmits only textual            information to a store website, such as “where's the tea            isle in this store?”, the response to the user may be            in-store directions and/or an in-store map showing the user            where the tea (e.g., the desired item) is, e.g., from the            user's location. Accordingly, as in (ii) above, the user may            be provided with a timely response without having to hunt            down store personnel.        -   (iv) The user may receive one or more electronic incentives            to purchase additional items at the store or from the            store's website. In particular, such incentives can be            customized to what the user is likely to need or desire            given, e.g., what the user has currently and/or previously            provided to the store's website. Moreover, such incentives            may also provide one or more of the following features:            -   (1) such an incentive may be dependent upon a return to                the store within a certain number of days and/or the                purchase of an additional item from the store or its                website;            -   (2) such an incentive may be forwarded by the user to                others; thus, the store's website is able to identify                additional potential customers by forwarding such                incentives;            -   (3) such incentives may be provided in conjunction with,                e.g., a game wherein the user plays the game for                determining the incentive. For example, the user may be                presented with a slot machine wherein the user can                activate the slot machine at most five times with the                incentive resulting from the last activation being the                incentive electronically provided to the user;            -   (4) such an incentive may be dependent on a location of                the user; for example, an incentive may be required to                be used prior to leaving the store or upon a return to                the store;            -   (5) such an incentive may be dependent upon on the user                listening to a presentation (e.g., in-store or on the                store's website) related to an item sold by the store;            -   (6) such an incentive may be specific to the                owner/subscriber of the MCD, wherein upon presentation                of the electronic incentive on the MCD, the user must                also present identification identifying him/herself;            -   (7) such an incentive may only become active when a                purchase from or a visit to an affiliated merchant is                made by the user; note that such visit may be readily                verified by the user activating the communications                network application on the user's MCD for locating the                user to thereby verify that at least the user's MCD is                located at the affiliated merchant;            -   (8) such an incentive may change its discount or                compensation to the user depending upon what the user is                about to purchase or information the user has                discovered; for example, if the incentive is for 20% off                a particular television and the user transmits a photo                to the communications network application showing a                lower price on the same television at a competing                merchant, then the incentive may be changed so that the                incentive when applied makes the purchase of the                television lower than that of the competing merchant.                Accordingly, while the user is in the competing                merchant's store, the user may receive a modified                incentive that provides incentive for the user to return                to the merchant providing the incentive and purchase the                television. Alternatively/optionally, the incentive may                be changed so that upon purchase of the television that                the user may be provided with additional services such                as an extended warranty;            -   (9) such an incentive may change depending upon                purchases by other users to whom the incentive may be                forwarded; in particular, since each such incentive may                include information about a user that forwards the                incentive, when such an incentive is submitted at a                store for redemption, one or more forwarding users may                also receive additional compensation. Accordingly, the                forwarding or distribution of incentives to other                communications network application users who will accept                such forwarding can be beneficial to the forwarding                user. Note that in the present context, a particular                incentive could rapidly travel through a network of                communications network application registered users.                Moreover, in a related aspect, a user may wish to                forward an incentive and also forward his/her benefit                (or a portion thereof) for forwarding the incentive.                Thus, such forwarding provides extra benefits for the                receiver. Further note that certain restrictions may be                placed on such forwards such that additional benefits                for forwarding are not provided if the receiving user's                MCD is:                -   (i) registered to the same wireless carrier                    subscriber as the forwarding MCD; and/or                -   (ii) is in a chain of MCDs receiving the forwarded                    incentive, and the MCD (or another MCD registered to                    the same wireless carrier subscriber as the MCD)                    previously forwarded the incentive;            -   (10) Such an incentive may be used to benefit a single                charity or organization. For example, for each time a                particular incentive is used in purchasing an item, a                benefit accrues to the charity or organization.

In another aspect, since a user may have a potentially large number ofincentives available for various merchants, the user's location atvarious times may be used identify the functionality of theincentive(s).

The present disclosure has been presented for purposes of illustrationand description. Further, the description herein is not intended tolimit the present disclosure to the form disclosed herein. Consequently,variation and modification commiserate with the above teachings, withinthe skill and knowledge of the relevant art, are within the scope of thepresent disclosure. The present disclosure is further intended toexplain the best mode presently known of practicing the invention asrecited in the claims, and to enable others skilled in the art toutilize the present disclosure, or other embodiments derived therefrom,e.g., with the various modifications required by their particularapplication or uses of the present disclosure. In particular, regardingthe various communication network applications recited hereinabove, suchcommunications network applications may be combined into a singlenetwork service, or provided individually.

What is claimed is:
 1. A method for locating a mobile station usingwireless signal measurements obtained from transmissions between saidmobile station and a plurality of fixed location communication stations,wherein each of said communications stations includes one or more of atransmitter and a receiver for wirelessly communicating with said mobilestation, comprising: providing first and second mobile station locationevaluators, wherein said location evaluators determine informationrelated to one or more location estimates of said mobile station whensaid location estimators are supplied with data having values obtainedfrom wireless signal measurements obtained via transmissions betweensaid mobile station and the communication stations, wherein: (A) saidfirst location evaluator performs one or more of the followingtechniques (i), (ii) and (iii) when supplied with a correspondinginstance of said data: (i) a first technique for determining, for atleast one of the communication stations, one of: a distance, and a timedifference of arrival between the mobile station and the communicationstation, wherein said first technique estimates a time of arrival (TOA)of a received signal relative to a time reference at each one of aplurality of wireless signal monitoring stations using an inversetransform whose resolution is greater than Rayleigh resolution; (ii) asecond technique for estimating a location of said mobile station, usingvalues from a corresponding instance of said data obtained from signalsreceived by the mobile station from one or more satellites; (iii) athird technique for recognizing a pattern of characteristics of acorresponding instance of said data, wherein said pattern ofcharacteristics is indicative of a plurality of wireless signaltransmission paths between the mobile station and each of one or more ofthe communication stations; and (iv) a fourth technique for estimating alocation of said mobile station using a USW model, wherein the followingsteps (a)-(d) are performed: (a) receiving at an antenna array providedat one of the communication stations, signals originating from themobile station, wherein the signals comprise p-dimensional array vectorssampled from p antennas of the array; (b) determining from the receivedsignals, a signal signature, wherein the signal signature comprises ameasured subspace, wherein the array vectors are approximately confinedto the measured subspace; (c) comparing the signal signature to adatabase comprising calibrated signal signatures and correspondinglocation data, wherein the comparing comprises calculating differencesbetween the measured subspace and calibrated subspaces; and (d)selecting from the database a most likely calibrated signal signatureand a corresponding most likely location of the mobile station by usingthe calculated differences; (v) a fifth technique for estimating alocation of said mobile station using an E model, wherein the followingsteps (a)-(e) are performed: (a) receiving, at a multiplicity of thecommunication stations, a signal transmitted by the mobile station; (b)forwarding, by each of a multiplicity of the communication stations,said received signal and timing information to a central processingcenter; (c) calculating, within said central processing center, a timedifference of arrival (TDOA) location estimate of said mobile stationbased upon said timing information; (d) calculating, within said centralprocessing center, a timing advance (TA) location estimate of saidmobile station based upon said timing information; and (e) determiningsaid position of said mobile station using said TDOA and TA locationestimates; (vi) a sixth technique for estimating a location of saidmobile station using an ST model, wherein the following steps (a)-(e)are performed: (a) receiving, in a SPS receiver co-located with themobile station, SPS signals from at least one SPS satellite; (b)transmitting cell based communication signals between: a communicationssystem having a first of the communication stations coupled to said SPSreceiver, and a second of the communication stations which is remotelypositioned relative to said mobile station, wherein said cell basedcommunication signals are wireless; (c) determining a first timemeasurement which represents a time of travel of a message in said cellbased communication signals in a cell based communication system havingat least some of the communication stations which comprises said secondcommunication station and said communication system; (d) determining asecond time measurement which represents a time of travel of said SPSsignals; (e) determining a position of said mobile station from at leastsaid first time measurement and said second time measurement, whereinsaid cell based communication signals are capable of communicating datamessages in a two-way direction between said first cell basedtransceiver and said communication system; (vii) a seventh technique forestimating a location of said mobile station using an TE model, whereinthe following steps (a)-(l) are performed: (a) transmitting from saidmobile station M samples of a signal; (b) receiving at one of thecommunication stations, said M samples together with multipathcomponents and noise; (c) determining an estimated channel power profilefor each of said M samples; (d) selecting a first set of N samples fromsaid M samples; (e) performing incoherent integration for said estimatedchannel power profiles for said first set of N samples to form a firstintegrated signal; (f) if a quality level of said first integratedsignal with respect to signal to noise is less than a predeterminedthreshold, selecting another sample from said M samples; (g) performingincoherent integration for said estimated channel power profiles forsaid first set of N samples and said another sample to form a secondintegrated signal; (h) if a quality level of said second integratedsignal with respect to signal to noise is greater than or equal to saidpredetermined threshold, determining a time-of-arrival of a maximumlevel of said second integrated signal; (i) entering saidtime-of-arrival into a time-of-arrival versus frequency of occurrencearray; (j) selecting a second set of N samples from said M samples; (k)repeating all of said performing through said entering steps for saidsecond set of N samples; and (l) determining a minimum value estimatedtime-of-arrival from said array; (viii) an eighth technique forestimating a location of said mobile station using an SigT model,wherein the following steps (a)-(e) are performed: (a) within the mobilestation, transmitting a locating signal composed of at least two tonecomponents; (b) within each of a plurality of the communicationstations, receiving the locating signal at one or more antennas, andwithin at least one of the communication stations, receiving thelocating signal with at least two antennas; (c) coupling each antenna toa receiver; (d) within each receiver, generating amplitude and phasevalues from the locating signal as received by the antenna, the valuesindicative of amplitude and phase of at least two tone components of thelocating signal, as received at the corresponding antenna and measuredat defined times; and (e) combining the values indicative of amplitudeand phase for the tone components from a plurality of the receivers todetermine the position of the mobile station; (ix) an ninth techniquefor estimating a location of said mobile station using a TLME model,wherein the following steps (a)-(h) are performed therefor in a mobileradio system providing at least some of the communication stations, saidmobile radio system including a network controller and at least three ofthe communication stations, each of said at least three communicationstations including an uplink TOA measuring unit operable to communicatewith said network controller, a control unit, and a time reference unitoperable to provide timing reference signals to said uplink TOAmeasuring unit, at least one of said at least three communicationstations co-located with and connected to a second mobile station, saidsecond mobile station coupled to said network controller via a radiointerface, and a service node operable to store known positions of atleast two of said at least three communication stations: (a) receiving arequest in said mobile radio system to determine the geographicalposition of said mobile station; (b) determining and reporting theposition of said second mobile station to said service node; (c)directing said mobile station to transmit digital signals uplink on atraffic channel when said mobile station is not transmitting ortransmitting only analog signals; (d) measuring in each uplink TOAmeasuring unit an uplink TOA of the digital signals transmitted by themobile station; (e) receiving in said network controller said uplink TOAmeasurements from said at least three communication stations and atraffic channel number to said traffic channel; (f) translating saidtraffic channel number to an identity of said mobile station; (g)conveying said uplink TOA measurements and said mobile station identityto said service node; and (h) calculating in said service node theposition of said mobile station using said known positions of said atleast three communication stations and said uplink TOA measurements; (x)a tenth technique for estimating a location of said mobile station usingan N model, wherein the following steps (a)-(d) are performed: (a)receiving global positioning system satellite (GPS) signals from aplurality of global positioning system satellites; (b) receiving aplurality of cellular position signals that do not contain data in aGPS-like format; (c) calculating the geographic position of the mobilestation using said received global positioning system satellite signalswhen a requisite number of the plurality of global positioning systemsatellites are in view of a global positioning system receiver; and (d)calculating the geographic position of the mobile station using bothsaid received plurality of cellular position signals and substantiallyall of said received global positioning system satellite signals whenthe requisite number of the plurality of global positioning systemsatellites are not in view of the global positioning system receiver;(B) for at least a particular one of said techniques performed by saidfirst location estimator, said second location evaluator performs adifferent one of said techniques when supplied with a correspondinginstance of said data for the different technique; first generating, bysaid first location estimator, first location related information thatis dependent upon an availability of a first corresponding instance ofsaid data; second generating, by said second location evaluator, secondlocation related information that is dependent upon an availability of asecond corresponding instance of said data; determining a resultinglocation estimate of the mobile station dependent upon at least one of:(a) a first value obtained from said first location related information,and (b) a second value obtained from said second location relatedinformation.
 2. A method as claimed in claim 1, wherein said steps ofclaim 1 are performed for a single emergency response request.
 3. Amethod as claimed in claim 1, further including a step of outputting, toan emergency response center, said resulting location estimate of saidmobile station in response to said emergency response request.
 4. Amethod for locating a mobile station using wireless signal measurementsobtained from transmissions between said mobile station and a pluralityof fixed location communication stations, wherein each of saidcommunications stations includes one or more of a transmitter and areceiver for wirelessly communicating with said mobile station,comprising: providing first and second mobile station locationevaluators, wherein said location evaluators determine informationrelated to one or more location estimates of said mobile station whensaid location estimators are supplied with data having values obtainedfrom wireless signal measurements obtained via transmissions betweensaid mobile station and the communication stations, wherein: (A) saidfirst location evaluator performs one or more of the followingtechniques (i), (ii) and (iii) when supplied with a correspondinginstance of said data: (i) a first technique for determining, for atleast one of the communication stations, one of: a distance, and a timedifference of arrival between the mobile station and the communicationstation, wherein said first technique estimates a time of arrival (TOA)of a received signal relative to a time reference at each one of aplurality of wireless signal monitoring stations using an inversetransform whose resolution is greater than Rayleigh resolution; (ii) asecond technique for estimating a location of said mobile station, usingvalues from a corresponding instance of said data obtained from signalsreceived by the mobile station from one or more satellites; (iii) athird technique for recognizing a pattern of characteristics of acorresponding instance of said data, wherein said pattern ofcharacteristics is indicative of a plurality of wireless signaltransmission paths between the mobile station and each of one or more ofthe communication stations; and (B) for at least a particular one ofsaid techniques performed by said first location estimator, said secondlocation evaluator performs a different one of said techniques whensupplied with a corresponding instance of said data for the differenttechnique; first generating, by said first location estimator, firstlocation related information using an available first correspondinginstance of said data; second generating, by said second locationevaluator, second location related information using an available secondcorresponding instance of said data; determining a resulting locationestimate of the mobile station dependent upon at least one of: (a) afirst value obtained from said first location related information, and(b) a second value obtained from said second location relatedinformation.
 5. The method as claimed in claim 4, wherein one or more ofsaid mobile station location evaluators generates a location estimate ofsaid mobile station.
 6. The method as claimed in claim 4, wherein saidmobile station is co-located with a processor for activating at leastone of said location estimators.
 7. A method for providing for each of aplurality of wireless mobile units, corresponding one or morenotifications related to an event or circumstance, wherein there is anetwork having a plurality of geographically spaced apart stationarynetwork access units for receiving wireless signals from the mobileunit, comprising performing, for each mobile unit, M, of the mobileunits, the following steps by computational equipment: (a) receivingnetwork input by a subscriber to a service for providing thecorresponding notifications for M, the network input for providing adata content in a persistent data storage, the data content used fordetermining the corresponding notifications; wherein the data contentincludes: (i) an identification of at least one entity authorized by thesubscriber to be notified of an occurrence of the related event orcircumstance, and (iii) one or more notification criteria whoseevaluation is for determining whether an occurrence of the related eventor circumstance has occurred; (b) subsequently, receiving informationindicative of a location for the mobile unit M, wherein the informationis determined using geolocation indicative measurements of wirelesssignals communicated between the mobile unit M and the network; (c)using an identification for the mobile unit M to access the data contentin the persistent data storage for evaluating the notification criteriausing the information; and (d) when the notification criteria evaluatesto a first result, a step of notifying the at least one entity by anetwork transmission of an occurrence of the event or circumstance andlocation information indicative of a location of the mobile unit M,wherein the location information is determined using geolocationindicative measurements of wireless signals communicated between themobile unit M and the network.
 8. The method of claim 7, wherein for atleast one of the mobile units, the corresponding event or circumstanceincludes an availability of a parking space, and one of thecorresponding notifications is transmitted to the at least one mobileunit.